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Link: https://www.thelec.net/news/articleView.html?idxno=14744

OmniVision Overtakes Samsung in Global CIS Market With 13% Share

According to an analysis by Chinese semiconductor news outlet ijiwei (爱集微), based on data from Japanese market research firm Techno Systems Research (TSR), OmniVision captured 13% of the global CIS market by revenue in 2025, surpassing Samsung Electronics’ 12.8% share for the first time. Sony retained the top position with a 54% share. 

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New Product Release – Image sensor for single-use medical endoscope IMX742

Ultra-compact and long-distance digital transmission Image sensors for single-use medical endoscopes
1/17.7” 0.51 MP IMX742 

Product page: https://www.sony-semicon.com/en/products/is/medical/endoscope/IMX742.html

Sony's IMX742 image sensor for endoscopes is designed for installation at the distal end of single-use (disposable) medical endoscopes. To help prevent infection transmission and improve workflow efficiency, demand is growing for single-use endoscopes, particularly those that require compact sensor sizes compatible with increasingly small diameter insertion parts, as well as high image quality, stable signal transmission, and other performance improvements.

The IMX742 is a CMOS image sensor that can meet these requirements. It is the first in the industry to achieve 5 m long-distance transmission with an ultra-compact size of 1 mm × 1 mm and a high digital image resolution of approximately 0.51 effective megapixels. The noise resistance and excellent S/N performance that can only be achieved with such digital output allows this sensor to provide high-visibility imaging even in low-light environments. Further, the IMX742 uses proprietary bi-directional communication technology to both reduce the pin count and achieve stable image transmission. This contributes to device miniaturization and improved performance, meaning the IMX742 can be mounted on small-diameter endoscopes that are less invasive for patients during testing and procedures in medical settings.

The ultra-compact design achieved with the IMX742

Device structure: Back-illuminated structure
Image size Diagonal: 1.02 mm (Type 1/17.7)
Effective pixels: 720 (H) × 720 (V)
Approx. 0.51 megapixels
Unit cell size: 1.00 μm (H) × 1.00 μm (V)
Chip size: 1.00 mm (H) × 1.00 mm (V)
Frame rate: 30 fps / 60 fps
Power supply: 2.7 V / 1.2 V / -1.2 V
Shutter mode: Rolling shutter, Global reset
Input/output interface: Bi-directional communication
Filter: Bayer
CRA: 30 deg
Package: 6-pin, WCSP

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Workshop page: https://sensorsmeetvision.github.io/smv2026/

Unconventional Image Sensors Meet Computer Vision

A workshop at ACCV 2026, the 18th Asian Conference on Computer Vision, held in conjunction with the International Workshop on Image Sensors and Imaging Systems (IWISS) 2026 — bringing the Asia-Pacific image-sensor community and the computer-vision community into the same room.

14 December 2026 from 9:00 – 17:15 in Room 1007 Grand Cube Osaka

Format Invited talks + posters 

Most computer-vision venues treat the image sensor as a fixed, conventional RGB camera. But a new generation of image sensors is rapidly reshaping what can be measured and, in turn, what vision algorithms can achieve.

This workshop focuses on the co-design of unconventional image sensors and the computer-vision and computational-imaging methods they enable. Its central premise is bidirectional: novel sensors give rise to novel CV/CI methods, and the demands of CV/CI in turn drive new sensor designs. Unusually for a computer-vision venue, sensor-hardware researchers are part of the organizing team, so the program reaches down to the device level rather than treating sensing as a fixed front end.

The workshop is the first of its kind at ACCV, and is held in conjunction with IWISS 2026, the biennial International Workshop on Image Sensors and Imaging Systems. Co-locating the two events connects an established sensor-side international community — much of the world's image-sensor industry sits in the Asia-Pacific region — with the computer-vision community.

09:00 – 09:10    Opening remarks
09:10 – 10:25    Session 1
09:10 – 09:35    Event-based Photometric ImagingBoxin Shi (Peking University, China)
09:35 – 10:00    A Fully Reconfigurable Hybrid SPAD Vision Sensor Featuring Time-Coded Dual ExposuresSeong-Jin Kim (Sogang University, Korea)
10:00 – 10:25    SPAD Vision Chips with Near-Sensor Spiking Neural Network ProcessingLiyuan Liu (Chinese Academy of Sciences, China)
10:25 – 10:50    Coffee break
10:50 – 12:05    Session 2
10:50 – 11:15    Design and Implementation of Task-Specific Lensless Cameras (tentative)Seung Ah Lee (Seoul National University, Korea)
11:15 – 11:40    3D Integrated Image Sensors and Flexible Image Sensors by Using SOI TechnologyMasahide Goto (Toyohashi University of Technology, Japan), Shigeyuki Imura and Hiroto Sato (NHK Science & Technology Research Laboratories, Japan)
11:40 – 12:05    Processing-in-Sensor: From Imaging to IntelligenceChih-Cheng Hsieh (National Tsing Hua University, Taiwan)
12:05 – 13:30    Lunch
13:30 – 14:20    Session 3
13:30 – 13:55    Thermal and Transient Imaging for Scene Understanding (tentative)Kenichiro Tanaka (Ritsumeikan University, Japan)
13:55 – 14:20    Securing Vision at the Sensor: PUFs and Adversarial Example DefenseShunsuke Okura (Ritsumeikan University, Japan)
14:20 – 15:50    Poster session (with coffee break)
15:50 – 17:05    Session 4
15:50 – 16:15    Computational Imaging with Single-Photon Cameras (tentative)Kaushik Mitra (Indian Institute of Technology Madras, India)
16:15 – 16:40    Title to be announcedYoungcheol Chae (Yonsei University, Korea)
16:40 – 17:05    A 1.494-µm-Pixel CMOS Image Sensor with Cluster-Level ADC and Motion Compensation for Global-Shutter-Equivalent Imaging in Mobile ApplicationsSanggwong Lee (Samsung Electronics, Korea)
17:05 – 17:15    Closing remarks 

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Link: https://www.thelec.net/news/articleView.html?idxno=15179

Samsung Electronics to Exit 8-Inch Foundry Business by 2030

Company notifies customers of shutdown plans, leaving fabless chipmakers scrambling for alternative production capacity

South Korean fabless semiconductor companies that rely on Samsung for chip manufacturing are now scrambling to secure alternative production capacity.

Industry participants are also calling for Samsung Electronics to delay the closure of its 8-inch production lines. They argue that government intervention may be necessary because individual fabless companies have little leverage to change Samsung’s decision to end production. 

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In a paper titled "A Programmable Readout Pixel Image Sensor" Lazzaro et al. from Dartmouth write:

In this paper, a pixel architecture that can be re-programmed to favor low noise, high speed, high dynamic range, or other characteristics desired in scientific imaging is proposed. Termed a programmable readout (PRO) pixel, this novel design combines a pinned photodiode, a deep-buried-channel CCD router, and multiple in-pixel amplifiers of different characteristics. By clocking the CCD router with different sequences, photogenerated charge can be steered to an appropriate readout amplifier given the application. The CCD router can be further programmed to store charge from multiple frames. The concept of such a pixel and its operation are described in detail and TCAD simulations aid in this discussion. To demonstrate this concept of programmability, a test chip is made with a CCD router and two in-pixel amplifiers: a floating diffusion amplifier (FDA) for fast readout and high-illumination imaging and a floating gate amplifier (FGA) for a low-noise Skipper-in-CMOS readout for low-light imaging. The test chip contains a 36 × 94 array of 20 µm pixels and contains 9 different pixel variants for experimental analysis. At the end of the paper, preliminary images captured from the different amplifiers are presented which demonstrate the ability to move charge to the selected readout while showcasing the different output characteristics of the two readout amplifiers. Furthermore, the output image from the Skipper-in-CMOS is compared across different numbers of non-destructive samples to demonstrate its noise-reduction capability.

Open access link: https://www.mdpi.com/1424-8220/26/16/5245

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The IEEE Jun-ichi Nishizawa Medal was presented to Eric R. Fossum at the 2026 IEEE Honors Ceremony for the invention, development, and commercialization of the CMOS image sensor. 

The ceremony was held on 24 April 2026 in New York City.

The IEEE Jun-ichi Nishizawa Medal is given for outstanding contributions to material and device science and technology, including practical application.

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STMicroelectronics introduces automotive image sensor to help scale affordable in-cabin sensing  

Helps OEMs and Tier 1s bring driver and occupant monitoring to high-volume vehicle platforms with lower system cost 

Delivers 35% higher image sharpness and nearly 60% higher infrared sensitivity than the previous generation in a compact 1.1 MP automotive image sensor 

STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, introduces ST SafeSense VD56GA, a new 1.1 MP automotive image sensor for infrared in-cabin sensing that helps OEMs and Tier 1 suppliers scale driver and occupant monitoring across vehicle lines while balancing performance, integration, and cost. 

As driver and occupant monitoring moves into more vehicle platforms, automotive manufacturers and suppliers are looking for imaging solutions that support strong in-cabin performance without adding unnecessary system cost or design complexity. VD56GA meets that need with a compact sensor architecture, high infrared sensitivity, and embedded image-processing features that can help simplify camera design and integration. The sensor is designed to give camera developers the image quality needed for driver and occupant monitoring while preserving the size and cost advantages of a compact format. In many in-cabin use cases, this can help customers meet performance targets without moving to a larger, more expensive sensor. 

“In-cabin sensing is moving beyond premium platforms, and carmakers need cost-effective solutions they can deploy broadly,” said Alexandre Balmefrezol, Executive Vice President and General Manager of the Imaging Sub-Group at STMicroelectronics. “With VD56GA, we focused on the system-level tradeoffs that matter most: image quality in infrared conditions, compact integration, and a cost structure that supports high-volume programs. Equally important, the sensor benefits from ST’s Integrated Device Manufacturer model, with front-end manufacturing in Crolles, France, giving customers greater supply-chain resilience, quality control, and long-term support for automotive programs.” 

“As driver and occupant monitoring systems move into a broader range of vehicle platforms, OEMs are increasingly focused on solutions that can be deployed at scale, with volumes set to exceed 70 million units by 2031. Success in this market depends not only on imaging performance, but also on reducing system cost, simplifying integration, and enabling adoption across high-volume vehicle programs," (*) underlined Anas Chalak, Market & Technology Analyst, Imaging at Yole Group.  

Helping carmakers scale driver and occupant monitoring 

VD56GA is designed to help reduce the cost of the complete camera module. Its imaging performance enables the use of lower-cost optics, simplified infrared illumination, less demanding optical filtering, and no external image-processing. For OEMs and Tier 1s, that can translate into a more cost-effective path to deploying driver and occupant monitoring across a broader range of vehicle programs. 

The sensor leverages a new backside-illuminated pixel architecture, called ST DeepNIR, optimized for infrared imaging. With 35% higher modulation transfer function (MTF) sharpness and nearly 60% higher quantum efficiency than the previous generation, VD56GA is currently the only sensor in its class to achieve this level of combined optical resolution and infrared sensitivity, helping in challenging conditions like under display camera. 

By extracting more performance from a compact 1.1 MP architecture, VD56GA helps automotive designers achieve the image quality required for advanced sensing functions, while benefiting from the integration and cost advantages of a compact sensor architecture.  

Compact integration with embedded image processing 

Designed for modern automotive camera modules, VD56GA is housed in a compact 3.7 mm x 3.2 mm CSP package, making it suitable for space-constrained installations and next-generation in-cabin camera designs. 

The device also integrates a range of embedded image-processing functions, including mirror, crop, dark calibration, auto exposure, and piecewise-linear processing. These features remove the need for external image-processing resources, simplify camera design and speed development. 

Support for both RAW and YUV output formats give OEMs and Tier 1 suppliers flexibility across different electronic architectures and software environments, making it easier to adapt the device to a broad range of implementation strategies. 

Building on ST’s automotive imaging leadership 

VD56GA builds on ST’s established presence in automotive imaging and in-cabin sensing. Earlier this year, ST announced shipment of its 10 millionth automotive of SafeSense by ST image sensors, reflecting broad adoption across key automotive regions, including Europe, Asia, and the United States.  

Customers benefit from ST’s vertically integrated manufacturing model and secure supply chain, with front-end manufacturing of VD56GA takes place at ST’s facility in Crolles, France and packaging in Asia; reinforcing the company’s focus on industrial resilience, product quality, and supply continuity for automotive customers worldwide. 

Availability 

Samples are available now. Pricing information and sample requests are available from local ST sales offices. 

Learn more: https://www.st.com/en/imaging-and-photonics-solutions/vd56ga.html

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Link: https://www.prnewswire.com/news-releases/leopard-imaging-and-lumotive-introduce-sirius-max--a-long-range-software-defined-3d-perception-platform-for-robotics-and-ai-302889658.html 

Leopard Imaging® and Lumotive Introduce "Sirius Max" -- A Long-Range Software-Defined 3D Perception Platform for Robotics and AI

 FREMONT, Calif., Sept. 24, 2026  -- Leopard Imaging®, a global leader in AI perception and spatial intelligence solution design and manufacturing, together with Lumotive, a pioneer in programmable optical semiconductor technology, today announced Sirius Max (LI-AR0234-AF0130-TX10-GMSL2-140H), a next-generation solid-state 3D LiDAR designed for advanced AI perception, robotics, industrial automation, autonomous machines, and intelligent edge systems.

Powered by Lumotive's programmable beam-steering technology and Leopard Imaging's high-performance embedded AI Perception expertise, Sirius Max delivers a compact, low-power, and software-defined 3D sensing solution optimized for next-generation machine vision and AI perception applications.

Sirius Max is Leopard Imaging's next-generation long-range RGB + depth perception platform, combining high-performance imaging, intelligent iToF depth sensing and processing, embedded synchronization, and programmable beam-steered illumination into a fully integrated GMSL2 camera system capable of real-time RGB-depth fusion and long-range active depth perception.

Unlike conventional flood-illumination ToF systems, Sirius Max utilizes directional beam steering to dynamically control illumination and depth scanning. This architecture significantly improves optical efficiency, ambient light rejection, signal-to-noise ratio, and long-range sensing performance while maintaining a fully solid-state design with no moving mechanical components.

The platform enables software-defined scanning and programmable sensing regions, opening new possibilities for intelligent perception systems in humanoid robotics, autonomous navigation, automotive monitoring, industrial automation, and smart infrastructure.

"Sirius Max represents a major advancement in programmable optical perception systems," said Bill Pu, CEO of Leopard Imaging. "By combining Leopard Imaging's AI perception and spatial intelligence expertise with Lumotive's breakthrough beam-steering technology, Sirius Max delivers long-range, software-defined 3D perception in a compact embedded platform. We are enabling AI systems to perceive farther, react faster, and perform more intelligent tasks with a single sensor platform."

"Leopard Imaging has extensive experience delivering high-performance embedded camera systems for AI and edge computing applications," said Apurva Jain, Senior Vice President of Product & Marketing at Lumotive. "Together, Sirius Max combines Lumotive's programmable beam-steering technology with Leopard Imaging's high-performance imaging platform to extend iToF sensing performance beyond 20 meters in both indoor and outdoor environments. With 1MP depth resolution and software-defined scanning capabilities, customers can leverage a single sensor platform for applications such as SLAM, collision avoidance, object handling, and navigation. Sirius Max enables AI systems to detect objects farther away, operate at higher speeds, and perform more intelligent tasks while reducing overall system complexity."

Advanced AI Perception Architecture

Sirius Max integrates synchronized RGB imaging, intelligent iToF depth sensing and processing, embedded processing, and Lumotive's TX10 programmable beam-steering transmitter into a compact GMSL2 camera module platform optimized for real-time AI perception workloads.

The platform supports synchronized RGB video, depth data, and control transmission over a single coaxial cable, simplifying integration into advanced embedded computing and edge AI systems. Through programmable scanning and region-of-interest control, Sirius Max can consolidate multiple sensing functions into a single camera platform. Customers can leverage one sensor for applications such as SLAM, cliff detection, collision avoidance, visual inspection, object handling, and navigation, reducing system complexity while improving performance and deployment flexibility.

Core technologies include

-   High-performance RGB imaging with integrated ISP
-   Intelligent iToF depth sensing based on the onsemi AF0130 depth sensor
-   Lumotive's LCM programmable beam-steering module

Key Features of Sirius Max

-   Solid-state wide-field-of-view RGB-D perception architecture
-   High resolution extended-range depth perception in indoor and outdoor conditions
-   Software-defined sensing in regions of interest
-   Compact, low-power embedded camera module design
-   Enhanced dynamic range, reduced multipath, and reduced saturation noise in all conditions
-   Embedded processing and synchronization
-   Low-latency GMSL2 connectivity
-   Optimized for robotics, industrial automation, automotive, and edge AI applications

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https://www.dpreview.com/articles/cmos-inventor-eric-fossum-helps-us-explain-lofic/

CMOS inventor Eric Fossum helps us explain LOFIC

 We worked with Prof. Eric Fossum to help explain the latest step forward in sensor design

It’s increasingly likely that you’ll have heard the term LOFIC, and some of the excitement around the capability it brings. We spoke to Professor Eric Fossum, inventor of the modern CMOS image sensor, who turns out to have some involvement in the early development of the concept, to explain how it works and what it could mean for cameras in future.

LOFIC stands for Lateral OverFlow Integration Capacitor and is a different way of designing pixel circuitry that allows them to capture more light. Conceptually, it stems from a similar idea to the dual conversion gain sensors we’ve seen over the past 12 years, but the benefits it promises appear even greater.

Fossum, now a Professor at Dartmouth College, uses the metaphor that capturing light is like collecting rainwater in a series of containers or buckets.

We’re going to slightly complicate the metaphor to encompass the concept of “conversion gain,” which is the relationship between the number of photoelectrons coming from the light-sensitive photodiode in each pixel and the size of the electrical voltage signal that’s then read out (measured in Volts per electron). 

In CMOS sensors, photoelectrons captured in a small bucket (smaller capacitance) give a proportionally bigger signal when read out than the same number would, if captured in a larger bucket (larger capacitance).

So a small bucket is well suited to low light (fewer photoelectrons) but you need a much larger one for capturing a lot of light, so that you don’t overfill the bucket.

In a LOFIC sensor, instead of one, we have both a small and a large bucket. The charge from the photodiode starts to collect in the small bucket, but if it exceeds its capacity, it overflows into the second, larger bucket. (Fossum called this “cascaded integration” in an early patent)

When it comes to readout, we measure the small bucket first. Because the charge was captured in a small bucket (with high conversion gain) we get a large signal that overwhelms any other noise that might get added later in the process. This gives us nice clean shadows and low-light images.

In a LOFIC sensor, we can then connect the two buckets together, combining their capacity (so, lower conversion gain) and adding in any overflowed charge. We then read out this combined signal. If we didn’t capture very much light, we can just use the first readout result. But if the small bucket was full, we can then use the second, combined readout, instead, giving us much more capacity for highlights.

Unlike the dual conversion gain system, Fossum points to the key benefit: “you don’t have to choose in advance.” And, as he points out, there’s no reason this system has to be limited to two buckets.

In practice, this means sensors that can tolerate a lot more light. And its implementation in relatively small, high-resolution sensors, suggests that space constraints aren’t a problem, at least not once you can use stacked sensor fabrication.

In the Osmo 4P we’ve seen DJI claim 17 stops of DR, which is an extraordinary number for a Type 1 sensor. This puts its DR on a par with much larger sensors (though doesn’t mean its image quality will match them). In its implementation, you can see how the additional dynamic range can be used.

The 4P’s camera that uses LOFIC technology is the only one that needs to use the new D-Log2 profile: a profile designed to accommodate more dynamic range. Interestingly, the base ISO of D-Log2 (the setting at which it captures maximum DR) appears to be 1600, suggesting that it’s being exposed to capture two additional stops of highlights compared with the ISO 400 base sensitivity of D-Log profile used for the conventional sensors.

However, the D-Log2 mode also lets you expose this same sensor state all the way down to ISO 100: clipping those additional highlights but using more exposure to capture the remaining tones, and thus boosting tonal quality. 

This gives us an idea of what LOFIC could bring to dedicated cameras: a choice of greater highlight capture or higher quality captures with the same highlight cutoff point as existing sensors.

After nearly a decade of sensors getting faster but not really offering improved image quality, LOFIC technology might be the step forward we’ve been waiting for.

Interestingly, Fossum – who is responsible for inventing the active pixel CMOS image sensor that virtually all modern cameras are based on – invented an early version of this concept, but the successors to the company he’d worked for instead concentrated their efforts on the simpler dual conversion gain system. A team at Tohoku University in Sendai, Japan, independently developed LOFIC as we’re now seeing it, citing Fossum’s Micron patent in their LOFIC patent, but proposing a more modern implementation.
 

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ISSCC 2027 is introducing a new Late Breaking News session to provide an opportunity for companies to showcase significant product announcements that missed the regular ISSCC submission deadline. This new session will feature four industry papers describing production-grade chips or IP blocks incorporated into products launching in 2027.

Please register your intention to submit by uploading a paper title and a short abstract by October 7, 2026 using the submission site below. The final manuscript is due by December 1, 2026, after which papers will undergo an expedited review process, with acceptance notifications issued on December 9, 2026. This track is limited to four accepted papers and is reserved exclusively for production-grade industry submissions covering products launching in 2027.

The submission site and key dates are summarized below.

Submission Site

https://submissions.mirasmart.com/ISSCC2027


Key Dates

    October 7, 2026 — Intent-to-submit deadline
    December 1, 2026 — Paper submission deadline (camera-ready format)
    December 9, 2026 — Industry committee review and selection; notifications sent for the four accepted papers
    December 14, 2026 — Final accepted papers approved by the ISSCC Editorial Team
    December 14, 2026 — Session summary due for the Advanced Program
     

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Link: https://www.image-sensors.com/image-sensors-asia/agenda?EventId=21998 

Day 1 Oct 28, 2026

9:00am
Session 1: Market Trends & Next-Generation CMOS Image Sensors
CMOS Image Sensors: Linking Market Evolution with Teardown and Reverse Engineering Analysis
CMOS image sensors (CIS) are at the core of modern imaging systems, serving a wide range of applications from consumer electronics to automotive, security, and industrial markets. This presentation will begin with an overview of the CIS market, including its current value, key drivers, and a five-year forecast, highlighting the main trends shaping demand across applications. Beyond market analysis, Yole Group combines these insights with teardown and reverse engineering activities to closely track technology evolution and industry changes. By dismantling commercial devices from system level down to the semiconductor level, it is possible to identify key design choices, integration approaches, and process technologies used by leading players. The presentation will illustrate how products are analyzed from full device teardown to cross-sectioning and physical analysis to extract detailed information on sensor architecture, stacking, and integration. This approach provides a practical and up-to-date view of the CIS ecosystem, linking market trends with real product implementation.
Bullets: • CIS market overview and 5-year forecast • Key application and demand trends • Teardown and reverse engineering methodology • From system dismantling to cross-section and physical analysis • Linking market insights with real device analysis
 
Anas Chalak | Market & Technology Analyst – Imaging, Yole Group
9:30am
Asian Suppliers Reshaping the Image Sensor Market: Driving the Next Phase of Growth and Competition
The global image sensor market is undergoing a significant shift, with Asian suppliers playing a central role in this transformation. This presentation examines key market dynamics, technology evolution, and demand across mobile, automotive, and security applications, highlighting how Asian suppliers are strengthening their competitive positioning and driving the next phase of market growth.
 
Jeffrey Mathews | Senior Analyst, TechInsights
10:00am
Networking Coffee Break
10:45am
From Eye to Intelligence — Where Next-Gen Image Sensors Must Go
Image sensors have always been measured by how well they serve the human eye — resolution, color accuracy, low-light performance, and dynamic range that translates to a beautiful photograph or video. That mandate isn't going away. Users still expect stunning capture from every camera they carry. But a new, parallel demand has emerged: the same sensor must now also serve as the front-end for machine intelligence — powering real-time scene understanding, contextual AI, and spatial computing in form factors that are always on and severely constrained. The next generation of image sensors must therefore serve two audiences simultaneously: the human viewer who expects premium image quality, and the AI pipeline that requires temporal consistency, power-efficient readout, and perceptual richness beyond what any display can render. In this talk, we explore how sensors are deployed today across both photography and AI workloads, where the tensions and synergies lie between these dual objectives, and what architectural choices — from pixel design to readout strategy to on-sensor processing — will define sensors that excel at both. The challenge for our industry is no longer choosing between the eye and the algorithm. It's designing silicon that refuses to compromise on either.
 
Harish Venkataraman | Director of Camera and Sensing Architecture and Systems, Meta Inc.
11:15am
Session 2: Breaking the Performance Limits of CMOS Image Sensors
Advancement of LOFIC CMOS Image Sensor Technology
After twenty years since its introduction, LOFIC CMOS image sensor technology has become a foundational architecture for achieving high performance HDR imaging in both scientific and consumer applications. This presentation first reviews the fundamental structure, operating principles, and development history of LOFIC CMOS image sensors. It then highlights recent advancements, including improvements in low light and high illumination sensitivity, SNR enhancement, and integration with wide waveband detection, analog/digital global shutter functionality, and other emerging techniques. Finally, recent application examples employing LOFIC CMOS image sensors will be presented.
 
Rihito Kuroda | Professor, Tohoku University
11:45am
Networking Lunch Break
1:00pm
Colloidal Quantum-dot Based SWIR Image Sensing Technologies
Abstract to be updated
Jiwon Lee | Assistant Professor, POSTECH
1:30pm
Breaking the Boundaries of CMOS Sensors Performances
As imaging applications evolve, the demand for enhanced CMOS Image Sensor (CIS) sensitivity has become a key challenge. From low-light and high-speed capture to depth sensing, today’s passive imaging technologies rely heavily on the quality and capabilities of CMOS image sensors. Maximizing photon collection in both visible and near-infrared wavelengths is now essential to unlock new capabilities and deliver superior image quality — even in the darkest environments.
3L-OPTRONICS – standing for Low-Light Level Optronics – wants to democratize dual day / night vision through the development of a low-cost CMOS technology in both large public applications – smartphones, automotive – and specific applications – space, scientific instrumentation, industrial vision and defence. To address low-light imaging needs, our efforts are directed at incorporating high-performance, near perfect anti-reflective solution: black silicon. Black silicon is a wideband spectral and large angular acceptance anti-reflective technology resulting from random surface texturing. 3L-OPTRONICS integrates this technology on CIS by a patented process highly scalable industrially – from 8” wafers for in-house processing to 12” wafers for licensed foundries – without the need to modify the surrounded electronics and the pixel architecture, for both large and small pixels pitch.
Our latest experimental results on a 10µm pitch CIS optimized for visible imaging show a sensitivity improvement across the entire silicon absorption spectrum, notably by doubling quantum efficiency, with a minimum dark current degradation. One visual method for revealing the added value of black silicon in image sensor is to capture images at low light levels – in accordance with French night-time lighting standards. Through this study, we demonstrate that black silicon pushes the limits of CIS night vision capabilities from night level 3 – 10 to 2 mlux – to level 4 – 2 to 0.7 mlux. Based on these results, our simulations show that black silicon could also represent a breakthrough in efforts to reduce sensor power consumption and increase readout speed.
To push furthermore the night vision capabilities sensor’s limits, hardware processing is combined with in-house contrast enhancement and denoising image processing algorithms powered by AI. On this part, experiments have been made in real night-time conditions – estimated as night level 4 between 2 and 0.7 mlux – and give us the opportunity to compare the performance of software processing on a reference CIS and black silicon CIS. This study shows not only that black silicon pushes the limits of low-light imaging capabilities but also enhances AI performance on the resulting images.
Our research shows that black silicon is a real game changer of CIS performance limits thanks to its impact on the entire acquisition chain. The next step is to integrate it into CIS with smaller pixels and higher resolution to demonstrate its technological compatibility in the smartphone sector.
 
Ludovic Escoubas | CEO, 3L-OPTRONICS
2:00pm
Optics Innovations in Deep Sub-Micron Pixel Scaling and the Paradigm Shift to Meta-Optics
It covers optic tech development history of mobile image sensors into deep sub-micron, and the new introduction of meta-surface technology to overcome the limit of conventional sensor optic technology, and their recent published results, then conclude with a few published result of extreme pixel scaling possibility with meta optics technology as an outlook.
 
Dr. In-Sung Joe | Principal Engineer, Samsung Electronics
2:30pm
Networking Coffee Break
3:15pm
Session 3: Robotics Vision & Industrial Inspection - Building Eyes for Intelligent Machines
Semiconductor Inspection: The Image Sensor Advantage
As demand for greater precision and yield across the semiconductor value chain continues to rise, image sensors have become a critical enabling technology for advanced inspection and metrology systems. In this session, Xinyang Wang, Founder, Chairman and CEO of Gpixel Changchun Microelectronics Inc., will discuss the role of image sensors in semiconductor manufacturing, packaging, testing and PCB inspection, and examine the market opportunity they represent within the broader inspection equipment industry. He will also explore how evolving technologies, including advanced packaging and high-performance computing applications, are driving demand for higher-resolution and next-generation sensing solutions. The presentation will conclude with an assessment of the competitive landscape and Gpixel's positioning and advantages in this fast-growing market.
 
Dr. Xinyang Wang | Founder, Chairman and CEO, Gpixel Group
3:45pm
Topic to be confirmed
Speaker TBC
4:15pm
The Eyes of Physical AI: Why the Next AI Revolution Begins with Infrared Sensors
For decades, image sensors have helped machines see the world. The next era will require them to understand it.
As AI moves from the digital world into the physical world, machines will need more than visible images. They will need sensors that can reveal material properties, chemical signatures, moisture, temperature, hidden structures, and information that the human eye cannot see. Infrared imaging, particularly SWIR sensing, is emerging as a critical interface between AI and the real physical world.
In this presentation, James Lee, CEO of STRATIO, will discuss how infrared sensors and AI can together enable a new generation of Physical AI systems — from robotics, automotive, and industrial inspection to agriculture, recycling, defense, and consumer devices. The presentation will explore why the future of image sensors is not only about higher resolution or lower power, but about giving machines a deeper sensory understanding of the world.
 
Dr. JaeHyung Lee | CEO and Co-Founder , STRATIO, INC.
4:45pm
Panel Discussion: Vision for Intelligent Robotics
Robots are rapidly moving beyond structured industrial environments into warehouses, hospitals, retail stores, homes, and public spaces. To operate safely and autonomously, they require increasingly sophisticated vision systems capable of perceiving, understanding, and interacting with the physical world.
This panel will explore how advances in image sensors, 3D sensing, edge AI, and perception algorithms are enabling the next generation of intelligent robots. Industry leaders will discuss the sensor technologies shaping robotics, the challenges of machine perception in real-world environments, and the future roadmap for robot vision systems.
Key Audience Takeaways
 Technology roadmap for robot vision systems
 Future image sensor requirements for robotics
 Impacts of Robotics vision on image sensors, machine vision, industrial automation, and defense
 Emerging opportunities in industrial, service, and humanoid robotics
 The convergence of sensing, perception, and AI 

Day 2 Oct 29, 2026

9:00am
Session 4: SPAD, ToF and 3D Sensing Technologies
Hybrid Time-of-Flight Image Sensors for High-Image-Resolution LiDARs
Various types of time-of-flight (ToF) imagers, employing either direct ToF (dToF) or indirect ToF (iToF), have recently been developed to perform effectively outdoors under strong ambient light. dToF imagers are well placed for long-range applications but still have difficulty achieving high depth image resolution. In contrast, iToF imagers using short-pulse (SP) illumination are more effective outdoors under strong background light, owing to reduced in-pixel ambient-light charge acquisition shot noise, while providing high range-image resolution. This work presents a hybrid ToF (hToF) CMOS image sensor employing a compact 6-tap and one drain, lateral-drift-photodiode pixel designed with triple n-type doping and that attains a high image resolution of 720x488 pixels while retaining long-range capability, with 100 m outdoor range imaging demonstrated under 100 klux direct sunlight at 10 fps using range shifted multiple subframes. A linearization method for the pixel's linear-logarithmic response expands the dynamic range, enabling accurate depth imaging of highly reflective and retroreflective targets such as road signs. Scanning-illumination techniques greatly improve the signal-to-background noise ratio and enhance the depth resolution or reduce the light power intensity as well as mitigate multi-path problem. These approaches offer a practical path toward high-image-resolution LiDAR systems for several outdoor applications as well as marine-observation and underwater use.
 
Dr. Kamel Mars | Associate Professor, Shizuoka Institute of Science and Technology & Shizuoka University
9:30am
From Perception to Action: Closing the Gap for Physical AI
Physical AI is advancing rapidly, but a fundamental challenge remains: closing the gap between perception and action. Robots can increasingly sense and understand their surroundings, yet the time and uncertainty between seeing, interpreting, deciding, and acting still limit their ability to interact naturally and reliably with the physical world.

Closing this gap requires more than improvements in sensors, compute, or AI models independently. It requires a tighter, continuous feedback loop between sensing and action, where perception informs movement, movement influences what and how the system senses, and new observations immediately refine the next action.

This presentation explores how advances in image sensing, 3D vision, multimodal perception, Vision-Language-Action models, and world models are enabling this transition. It will also examine the critical role of simulation and synthetic data. Real-world human and robotic training data alone can never represent every environment, interaction, and edge case that physical AI will encounter. But simulation is only as useful as its representation of reality. Incorporating vision models grounded in real-world sensor data is critical to reproducing the visual and spatial conditions robots will actually encounter, including sensor characteristics, environmental variability, and challenging edge cases. This connection between real-world sensing and simulation enables more representative training and more meaningful validation before deployment.

By bringing real-world sensing, simulation, intelligence, and action closer together, the industry can move beyond robots that simply understand their environments toward machines capable of interacting with the physical world in real time.
 
Michael Nielsen | Chief Marketing Officer, RealSense
10:00am
Bringing Reliable 3D Perception to Robotics, AR/VR, and Beyond
A compact, fully integrated solid-state LiDAR sensor is increasingly important for applications in robotics, augmented and virtual reality, and agri-tech, where robust depth perception is essential for real-world understanding and interaction. We present a compact time-of-flight 3D LiDAR solution providing up to 2.3k depth zones and strong ranging performance even under high ambient illumination. The sensor is based on a 3D-stacked backside-illuminated SPAD architecture with a 10µm pitch and a 220 × 198 detector array. The pixels are grouped into 2 × 2 macropixels, yielding a native readout resolution of 110 × 96, with an additional test row resulting in a 110 × 98 physical array. The device is wafer-to-wafer stacked with integrated front-end circuitry, a flash time-to-digital converter, and integrating counters, enabling a compact and highly integrated depth-sensing platform. The module also integrates meta-surface optical elements for lensing, VCSEL IR light sources and a VCSEL driver for a truly all-in-one solution.
 
Duncan Hall | Product Marketing Manager, STMicroelectronics
10:30am
Networking Coffee Break
11:15am
Session 5: Breaking the Low-Light Barriers
From Emerging to Mainstream: SPAD Technology Trends and X-FAB's Innovation Platform
Single-Photon Avalanche Diode (SPAD) technology is undergoing a significant transition from enabling specialized applications to becoming a mainstream sensing solution across multiple industries. Advances in CMOS integration, array scaling, and system-level architectures have accelerated the adoption of SPAD-based image sensors well beyond traditional scientific and defense applications. Today, consumer electronics, automotive sensing, industrial inspection, healthcare, and quantum-related technologies are all contributing to the growing demand for high-performance SPAD platforms. As application requirements become increasingly diverse, foundry technologies play a critical role in enabling scalable and manufacturable SPAD solutions. The presentation will introduce X-FAB's SPAD technology platform and highlight recent innovations in device architecture and process integration that enable customers to develop next-generation SPAD image sensors for a wide range of applications.
 
Heming Wei | Technical Marketing Manager, X-FAB
11:45am
Networking Lunch Break
1:00pm
A Novel Starting Material for CMOS Image Sensors with Built-in gain Stage for Low Light Application
In this paper we present a novel concept for a new starting material for CMOS image sensors with superior low light performance. We propose an avalanche gain silicon sensor for image sensors, incorporating a continuous buried gain junction as starting material. The structure separates photon absorption, charge multiplication, and signal collection, enabling internal gain that is largely independent of the pixel architecture. This innovative separation of function supports smaller pixels and thinner absorption regions while improving signal-to-noise ratio and low-light sensitivity.
 
Benoit Dupont | CEO, Etesian Semiconductor
1:30pm
Session 6: Automotive Vision Systems
From Requirements to Reality: Rethinking Performance and Cost in Automotive Image Sensors
Automotive vision systems are evolving rapidly as vehicles transition toward higher levels of intelligence and automation. While demand for improved perception continues to grow, maximizing every image sensor specification no longer guarantees the best system value. The industry is shifting from pursuing peak performance to delivering the right performance—meeting application-specific requirements while optimizing cost, scalability, supply chain resilience, and time-to-market. This keynote explores how the industry is redefining image sensor requirements through scalable platform strategies that balance high dynamic range (HDR), low-light sensitivity, LED flicker mitigation, high speed interface standardization, frame rate, cybersecurity, power consumption, and edge-AI computing against system cost and supply chain resilience. The discussion will examine how common sensor architectures can support multiple vehicle programs while remaining adaptable to future perception algorithms and regulatory requirements. Ultimately, the next generation of automotive image sensors will be judged not by peak specifications, but by their ability to deliver the right performance, at the right cost, for safer and more intelligent mobility.
 
Dr. Hieu Tran | Technical Product Marketing, Ecosystem Platforms and OEMs, onsemi
2:00pm
CMOS Image Sensors and SPAD Direct ToF Sensors for Automotive Applications

    Introduction - Sony Group Corporation’s sales, automotive market trend, and Sony Semiconductor Solutions Corporation’s market share target
    CMOS Image Sensors - Customer expectations, product lineup, and introducing the latest products
    Functional Safety and Cybersecurity - ISO26262 standard, patent examples and product line-up
    SPAD Direct ToF Sensors - Customer expectations, product lineup, and introducing the latest products


Naoki Kawazu | Senior Analog Design Manager of Automotive Development Department, Automotive Business Division, Sony Semiconductor Solutions Corporation
2:30pm
From Embodied AI to Autonomous Driving — How Global Shutter Vision Sensors Empower Every Scene
Large foundation models are transitioning from the digital realm to the physical world, positioning vision sensors as the essential gateway for robots and autonomous vehicles to perceive and understand their surroundings. SmartSens' SmartGS™ global shutter technology, based on a BSI backside‑illuminated pixel architecture, ensures that all pixels are exposed simultaneously, effectively eliminating rolling shutter distortion and motion blur even during rapid movement. This is complemented by Micro‑Pillar™ near‑infrared enhancement for superior low‑light sensitivity, along with Knee Point HDR and InSensor HDR® innovations that deliver exceptional dynamic range in challenging lighting conditions. These capabilities enable robust performance across a wide range of applications—from V‑SLAM navigation, obstacle avoidance, and object manipulation in embodied robots, to driver monitoring, occupant sensing, and traffic perception in autonomous vehicles. SmartSens offers SmartGS™ global shutter sensors covering resolutions from 0.3MP to 14MP, tailored to meet the varied needs of different scenarios. By providing reliable, high‑quality visual data, our solutions empower intelligent systems to advance from mere functional tools to true cognitive partners in every scene.
 
Jessie Zhao | Marketing Manager, SmartSens Technology (Shanghai) Co., Ltd.
3:00pm
Session 7: Mobile Application Updates
From Image Sensor Innovation to Product Value
Smartphone cameras continue to evolve through the integration of advanced image sensors, optics, sensing functions, and AI-based image processing. As a result, it is becoming increasingly difficult to predict the contribution of an image sensor to the final user experience based solely on device-level specifications. At the same time, even promising sensor technologies with the potential to create significant value do not necessarily make their way into products.

In this talk, drawing on my experience in both image sensor development and smartphone camera development, I propose a “deep technical collaboration” in which current challenges and use cases from the smartphone camera side are shared early, together with a “customer-driven pull approach” to overcome these challenges. Using examples such as AF, color reproduction, OIS, and HDR, I will discuss the importance of evaluating the value of sensor technologies at the system level, rather than based solely on sensor performance. Furthermore, I will discuss a practical collaboration framework in which the results of joint evaluation are developed into joint demonstrations and proposals, necessary and sufficient performance targets are jointly defined, and the smartphone maker provides a clear “pull” (explicit demand from the customer side). This approach can reduce uncertainty in suppliers’ development and investment decisions and help drive decisions to initiate development and move new technologies toward productization.
 
Masahiko Nakamizo | Chief engineer, Honor Technologies Japan
3:30pm
Session 8: Camera Systems, Characterization & Integration
Beyond the Datasheet: EMVA 1288 as a Hardware Integration Diagnostic for Application-Grade Camera Systems
In application-grade camera development, a sensor that meets all datasheet specifications on an evaluation kit can exhibit significant, reproducible IQ degradation on a custom PCB and pass every post-ISP functional test undetected. The instinct is to blame ISP tuning. The root cause frequently lies upstream — and standard image quality benchmarking is structurally incapable of finding it. This presentation reports findings from a structured EMVA 1288 Release 4.0 characterisation study conducted on an identical AR0235 sensor across two hardware configurations at matched gain, exposure, and illumination conditions. Despite the sensor being common to both platforms, EMVA analysis revealed a 3.7× difference in dark current variance — 5.95 e⁻/s versus 21.8 e⁻/s — alongside a sign reversal in mean dark current, indicating a platform-dependent black level offset that ISP calibration would silently inherit. Dark-frame covariance analysis further revealed structured, platform-specific row-correlated noise that collapses to near zero at half-saturation — the exposure regime in which standard SNR and noise benchmarks are typically acquired. This exposure dependence is the precise mechanism by which post-ISP metrics can report equivalent performance across two hardware configurations while concealing fundamentally different sensor-level noise behaviours. These findings illustrate a repeatable diagnostic pattern: integration failures that are invisible to post-ISP sharpness and noise evaluation become immediately apparent in raw-frame EMVA measurements, specifically dark current variance, dark-frame covariance structure, and DSNU spatial frequency analysis. We present a practical pre-tuning gate methodology based on these measurements, expressed as platform deltas rather than absolute values, and discuss the conditions under which post-ISP metrics will and will not surface sensor-level integration pathology — including the role of ISP noise reduction kernel scale, black level calibration timing, and exposure-level selection...
 
Tina Agnes Ruth K | Senior Project Engineer - Imaging, e-con systems
 

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Several news outlets are reporting that OpenAI has bought computational photography startup Glass Imaging for ~USD 300 million. Glass Imaging develops AI algorithms that improve image quality from small image sensors such as those found on smartphones and mobile devices.

WSJ: https://www.wsj.com/tech/openai-buys-startup-developing-smartphone-camera-63590370 

TechCrunch: https://techcrunch.com/2026/09/14/openai-buys-smartphone-camera-maker-glass-imaging-for-300-million-report-says/

Yahoo Finance: https://finance.yahoo.com/technology/ai/articles/openai-acquires-glass-imaging-camera-134907735.html 

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Singular Photonics launches world-first SPAD-based image sensor

Litavis offers programmable multi-modal capabilities on-chip, accelerating time-to-market for imaging applications.

Edinburgh, UK – September 10, 2026 – Singular Photonics, an innovator in single-photon imaging, today announced the launch of its most advanced image sensor to date. Litavis is the world's first single-photon avalanche diode (SPAD) sensor using in-pixel processing to unify imaging, timing, histogramming and photon statistics on a single chip.

Designed to bring unprecedented flexibility and intelligence to imaging applications, Litavis introduces a software-configurable sensing architecture capable of combining photon-counting imaging, programmable time gating, and advanced photon timing within a scalable SPAD array platform.

Litavis is also the first SPAD-based sensor to enable simultaneous intensity, timing and histogramming modes. The system also enables users to dynamically adapt sensor parameters in software without requiring new hardware designs.

By processing photon events directly on-chip, Litavis significantly reduces the amount of raw data that must be transferred and processed externally. This enables more scalable real-time imaging systems through lower latency, improved power efficiency and faster decision-making.

Litavis supports a broad suite of configurable operating modes, including:

•  Multiple TCSPC and high throughput TDC configurations using internal or external clocks
•  High-dynamic-range photon counting modes with selectable resolution
•  Windowed and coincidence-based detection for advanced temporal analysis
•  Combined timestamping and imaging modes

Developers can reconfigure the same hardware platform for different applications with minimal redesign effort, accelerating development cycles and reducing system complexity. The sensor is suitable for a broad range of applications including machine vision, robotics, physical AI, depth sensing, spectroscopy, scientific imaging, medical imaging, quantum technologies and industrial automation.

“Litavis combines the sensitivity advantages of SPAD technology with the adaptability and scalability increasingly required by modern multimodal imaging,” said Shahida Imani, CEO of Singular Photonics. “It condenses these into one intelligent sensor, enabling a new generation of imaging systems built on a single, configurable platform. We designed Litavis to serve multiple applications and markets, and we've already received significant pre-order volumes from companies and institutions around the world.”
As with Singular’s other products, Litavis is named after an ancient Celtic deity, an earth goddess, whose name means “the broad one” – reflecting the extensive capabilities of the new sensor.

Litavis will be demonstrated at SPIE Sensors + Imaging in Edinburgh next week, and at VISION, the world's largest machine vision tradeshow in Stuttgart in October.

Technical details
Litavis is a CMOS SPAD-based imaging sensor platform built on an architecture that combines single-photon sensitivity with integrated digital photon processing directly on-chip and in-pixel. This enables precise capture of spatial and temporal information, while reducing reliance on external processing hardware, allowing the sensor to extract additional scene information including depth, timing and event characteristics.

Litavis delivers continuous 256 × 256-pixel photon-counting imaging under low-light conditions. In parallel, time-stamped photon events are generated at a lower rate on a 64 × 64 macropixel grid, providing picosecond-resolution photon timing alongside full-resolution photon counting.

The sensor also supports multi-event timing, allowing multiple detected photons per excitation cycle to be individually time-binned, and in-pixel histogramming. These capabilities provide access to temporal statistics beyond conventional intensity measurements. This supports applications such as fluorescence lifetime imaging, dynamic light scattering, and quantum sensing.

Litavis integrates configurable acquisition and timing capabilities directly within the pixel array. This allows developers and system integrators to rapidly prototype, evaluate and deploy advanced imaging solutions using a single adaptable platform.

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Link: https://www.techtimes.com/articles/323736/20260810/sony-splits-sensor-manufacturing-tsmc-63b-deal-capture-physical-ai-market.htm

Some excerpts below. 

Sony Splits Sensor Manufacturing With TSMC in $6.3B Deal to Capture Physical AI Market
Joint Venture Keeps Pixel IP at Sony While TSMC Supplies Logic Process for Cars and Robots 

Sony Group and Taiwan Semiconductor Manufacturing Co. announced Monday that they plan to invest approximately ¥1 trillion (approximately $6.3 billion USD) in a joint venture to manufacture next-generation image sensors at Sony's Koshi City fab in Kumamoto Prefecture, with commercial production targeted for 2029, according to the Japan Times. The investment is not an incremental expansion of Sony's existing manufacturing footprint — it is an acknowledgment that the sensors required to power robots, autonomous vehicles, and AI-driven industrial systems operate on fundamentally different technical principles from the smartphone sensors that built Sony's 43% market lead, and that meeting those requirements demands a manufacturing partnership Sony cannot replicate alone.

Why Sony Could No Longer Do This Alone

[...] the sensors required for physical AI applications — cameras inside self-driving cars, robotic manufacturing lines, and industrial inspection systems — are a categorically different product from the sensors inside a smartphone, and building the manufacturing infrastructure to produce them at scale requires both the capital and the process technology that Sony's in-house fabs cannot provide on their own.

[The difference is threefold.]

The first is the global shutter. [...]

The second is dynamic range. [...]

The third is temperature tolerance and functional safety certification. [...]

What the Fab-Light Model Actually Splits

[...] Sony will not share [the pixel layer] manufacturing process with TSMC under the joint venture[...]. Sony retains full control of the pixel wafer.

The second wafer is the logic layer [which will benefit] enormously from advanced logic process technology [from] TSMC's logic process expertise, specifically its ability to manufacture the logic die at nodes Sony cannot match in-house [...].

The two wafers are then bonded using copper-to-copper hybrid bonding — a technique Sony pioneered for commercial image sensor production around 2016 [...].


The Sony-TSMC sensor joint venture supplies the perception layer that physical AI systems require. Whatever a robot or autonomous vehicle is doing with its AI model, it is perceiving the world through an image sensor first. 

Sony's IP Bet and the Competitive Clock

The joint venture is also, implicitly, a response to a competitive clock [...] Apple confirmed in August 2025 that it was working with Samsung at the latter's Austin, Texas facility [...].

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Open access paper link: https://www.cell.com/iscience/fulltext/S2589-0042(26)02211-X

Yoon et al., "Angle- and polarization-adaptive aperiodic-anisotropic metasurfaces for broadband reflectance suppression" iScience (2026)

Optical reflectance at the air-silicon interface degrades CMOS image sensor (CIS) performance, causing signal loss and image artifacts. Conventional single-layer anti-reflective coatings (1-ARCs) offer CMOS-compatible simplicity, but their isotropic nature and limited spatial tunability make them poorly suited to handle angle- and polarization-dependent characteristics of incident light, particularly where the chief-ray angle varies across the sensor surface. Here, we present an aperiodic-anisotropic metasurface (AAM) composed of subwavelength TiO2 nanodisks with spatially varying geometric anisotropy, enabling broadband, angle- and polarization-resolved impedance matching tailored to local incidence conditions. Its performance was verified through unit-cell-level optimization and further validated by full-area simulations on a 20 × 20 μm2 Si substrate under Gaussian beam illumination, where the AAM achieved ∼1.40% average reflectance across 400–700 nm for both polarizations, outperforming conventional 1-ARC and double-layer anti-reflective coating (2-ARC). This offers a practical solution for CIS and other systems such as LiDAR (light detection and ranging) receivers under spatially varying illumination. 

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https://www.sony-semicon.com/en/news/2026/2026072201.html

Mitsubishi Electric and Sony Semiconductor Solutions Agree to Establish a Joint Venture to Build AI Vision Sensor Solutions for Manufacturing Applications
To Enhance Recognition, Decision-Making and Control in Manufacturing and Contribute to Labor Savings and Unmanned Operations 

Mitsubishi Electric Corporation (“Mitsubishi Electric”) and Sony Semiconductor Solutions Corporation (“Sony”) have entered into a definitive agreement on a strategic partnership aimed at accelerating the automation and advancement of manufacturing equipment and manual operations in the manufacturing industry. Under the partnership, the two companies will establish a newly formed joint venture (“JV”), Advanced Vision Solutions Co., Ltd., which is scheduled to begin operations in October 2026, subject to the receipt of necessary approvals and clearances from relevant authorities.

Going forward, through the JV, the companies will develop and offer vision-sensor*1  solutions leveraging cutting-edge technologies that enable AI-based analysis of visual data directly on image sensors. The solutions will precisely capture conditions and changes across a broad range of manufacturing sites that have traditionally been difficult to visualize, and connect them to decision-making and control. They will support automation and autonomous operation of a wide range of manufacturing equipment, contributing to labor savings and unmanned operations.

This partnership will enable the two companies to integrate Sony’s industry-leading image sensors and edge AI technologies with Mitsubishi Electric’s extensive expertise in FA control systems cultivated over many years. The solutions will precisely capture conditions at manufacturing sites, product quality, equipment operations, and maintenance-related information that were previously difficult to fully understand and utilize. Furthermore, it will efficiently extract the necessary information from the acquired data and connect it to appropriate decision-making and subsequent control, enabling timely and autonomous improvements tailored to equipment and operational conditions with minimal manual intervention. 
In addition to vision data, the solutions will integrate with a variety of data from manufacturing sites, contributing to the development of multimodal production systems capable of detecting changes, early signs and other conditions that cannot be fully identified from a single type of data alone. Through this initiative, the companies aim to drive the deployment of physical AI in the FA domain and provide solutions that can be used without specialized expertise in optics or AI, across broad industries seeking labor savings, autonomous operations, quality improvement, and more advanced maintenance in production environments.

*1 Vision sensor: A high-precision sensor that captures images of products and parts on manufacturing lines using a camera and detects the condition and positional information of target objects in real time. By working in conjunction with factory automation (FA) equipment, it enables automation at manufacturing sites.

“Mitsubishi Electric has long provided a wide range of FA equipment to customers, primarily in the manufacturing sector,” said Takayuki Tsuzuki, Executive Officer (Associate); Group President, Factory Automation Systems at Mitsubishi Electric Corporation. “Today, the need for labor-saving, unmanned systems and autonomous optimization at production sites is greater than ever. Through this partnership with Sony Semiconductor Solutions, we will develop AI vision sensors as a new core component and build a new FA digital solutions business by integrating vision data with our digital platform, ‘Serendie™*2.’ Furthermore, by realizing advanced autonomous control with physical AI and other applications, we aim to provide new value to customers and address social challenges such as labor shortages.”

“Sony has contributed to solving challenges and creating new value across a wide range of industries by accurately capturing real-world information through edge‑AI sensing technologies centered on image sensors,” said Shinji Sashida, President and CEO of Sony Semiconductor Solutions Corporation. “Image sensors, which serve as the ‘eyes’ that generate vision data, play an important role in enabling AI to understand on-site conditions and connect them to decision-making and control. Through this partnership with Mitsubishi Electric, which has deep expertise and a strong customer base in the FA domain, we will bring solutions that leverage our sensing technologies to the market, create value across an even broader range of industries, and further accelerate the evolution of our sensing technologies.”

Company name: Advanced Vision Solutions Co., Ltd.
Business description: Development of AI-powered vision sensors and vision-sensor solutions for factory automation (FA)
Shareholding ratio: Mitsubishi Electric 60%, Sony Semiconductor Solutions 40% 

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Elio: https://www.eliolabs.com/technology 

News Link: https://www.businesswire.com/news/home/20260723118244/en/Elio-Raises-%2421M-to-Build-Sensing-for-the-AI-Era

SILICON VALLEY, Calif.--(BUSINESS WIRE)--Elio, a company building sensors designed for artificial intelligence rather than the human eye, today announced a $21 million funding round led by Innovation Endeavors and Xora, with participation from Kevin Weil and Scribble VC. Existing investors UpWest and Resolute Ventures, who led the company's previous round, are continuing their support.

Today's sensors capture one fixed view of the world, decided in advance, shaped by what the human eye can see rather than what a machine needs. Elio is changing that: its sensors let AI decide what to capture, in real time, based on what it is trying to figure out - delivering exactly the information needed, when it's needed, instead of a fixed picture to interpret after the fact.

The technology puts computation inside the optics itself. Before light reaches the sensor, dynamic optical layers of micromirrors process it directly - acting more like a neural network than a lens - pulling out signals a conventional lens would flatten and lose. AI learns how the optics behave and corrects them live, reading objects and materials by their physical signature, not just their pixels.

As a result, a single module can do the job of many, and it keeps gaining new abilities after it's already shipped. Sensing starts to behave like software: the same unit gets more capable over time, instead of becoming outdated.

Elio can be used in any context where sensing is required. In microscopy, Elio lets researchers watch living cells respond to a drug over time without staining or fixing the sample, work that today requires destroying the sample for a single datapoint. In semiconductors, Elio enables engineers to see through a chip's stacked layers to catch buried defects without cutting the wafer apart. In robotics, Elio gives machines multiple senses in one module that self-calibrates and switches as the scene changes. In defense, Elio can detect small, fast-moving threats like drones at long range across conditions such as darkness or haze that challenge even the best conventional sensors. Across every application, Elio is expanding the universe of what sensors are meant to do - building dynamic, real-time, label-free methods that capture the complexity of the real world and allow AI to find the patterns that matter.

Elio is led by Founder and CEO Nadav Grossinger and Chief Technology Officer Nitay Romano, who have worked at the intersection of optics and AI for more than 20 years. The two previously co-built Pebbles Interfaces, acquired by Meta, then spent seven years leading the physical-sensing stack behind Meta's AR and VR headsets. Grossinger's earlier ventures include ColoRight, acquired by L'Oréal. Romano, a leading figure in diffractive optics, previously served as Chief Optical Scientist at Holo/Or, the science underpinning Elio's core technology. 

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Link: https://novoviz.com/variable-frame-rate-spad-camera/

The NVx5VFR-HW variable frame rate camera was developed for applications requiring high sensitivity and/or frame rate but with reduced output bandwidth. The camera combines the benefits of a SPAD camera, namely the single-photon resolution and fast operating speeds, with those of an event camera—low output data rates. 

Features: 

• 480 x 320 or 256 x 192 SPAD pixels
• Event-based readout
• Adjustable event threshold
• 20ns global shutter
• On-chip pixel binning
• USB 3.0  

Event camera emulation
[...] because there is a single sensor and a single acquisition, the two modalities are inherently synchronized in time and space, without genlocking, cross-sensor calibration, or timestamp drift. The SPAD sensor thus functions as a flexible substrate that can be reprocessed into multiple imaging modalities entirely in software. 

HDR Imaging
[...] photon-counting approach lets each pixel build its own exposure curve, avoiding the clipping and noise floor issues that limit standard CMOS or CCD imaging. 

Instantaneous adaptation to lighting variation
[...] photon-counting approach lets the sensor adapt instantly to drastic lighting shifts, with no exposure recalibration, no motion blur, and no saturation, capturing both the bright and near-dark scenes with equal clarity in the same brief 2ms window. 

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Singular Photonics Lands Funding to Launch Next-Generation Image Sensors as Commercial Traction Grows

Fabless semiconductor startup appoints former Arm CTO to Board as demand for SPAD-based image sensors accelerates.

Edinburgh, UK – August 19, 2026 – Singular Photonics, a developer of SPAD-based image sensors, today announced it has closed an oversubscribed $2.15 million funding round, led by ACF Investors, with participation from Wren Capital, Cambridge Angels, Scottish Enterprise, Quantum Exponential and Old College Capital. The new capital will accelerate development of a new generation of sensors, expanding the company's product roadmap in response to demand from its growing customer base.
Singular has already doubled its full-year 2025 sales in 2026 to date, driven by customer engagements spanning multiple sectors, including a recent collaboration with instrumentation leader Renishaw. The investment will be used to scale engineering capacity and speed time-to-market for new image sensors capable of advancing new applications in markets ranging from machine vision, industrial automation and physical AI to scientific discovery and medical imaging.
 
“This has been a phenomenal year for Singular Photonics,” said CEO Shahida Imani. “We've already doubled our 2025 sales, we're approaching break-even, and our customers are telling us exactly what they want from future products. This oversubscribed round means we can respond faster – expanding our sensor portfolio and bringing new features to market on our customers’ timelines, not just our own.”
 
“Singular Photonics is an exciting addition to our portfolio, combining world-leading sensor science with genuine commercial promise,” said Tim Mills, Managing Partner at ACF Investors. “The industry is moving from capturing images to generating actionable insights directly from light itself, and Singular has both the technology and the team to lead that shift. We're delighted to back them into their next phase of growth.”
 
“Scottish Enterprise has supported Singular Photonics ambition to develop SPAD-based image sensors over several years,” said Derek Shaw, Director of Company Funding & Investment at Scottish Enterprise. “The Photonics, Quantum, Sensing and Connectivity and Semi-conductors Sector is a key opportunity area for growth for Scotland. Companies such as Singular Photonics can play a vital role in transforming our economy by scaling-up, creating high value jobs and competing internationally.” 
 
“In a strong signal of confidence in Singular’s trajectory, existing shareholders followed the new investors into the round, meeting or exceeding their pre-emption rights,” said Singular Photonics Chairman Pete Hutton. “Combined with the appetite shown by new investors, the round was met with robust demand – a clear vote of confidence in the team, the technology and the commercial momentum the company has built.”

Dipesh Patel joins Board
Singular also announced that Dipesh Patel, the former CTO of global semiconductor giant Arm, has joined the company’s board of directors. During his 25 years at Arm, Dr. Patel held a number of general and technical management positions culminating in his role as CTO where he was responsible for the Research and Digital IT functions.
 
“Singular Photonics is transforming image sensors from passive imaging devices into intelligent sensing platforms,” said Dr. Patel. “SPADs have long been viewed as highly sensitive photon-counting devices, but Singular is showing the world that a far greater opportunity is now emerging, and I’m looking forward to helping the company capitalise on that opportunity.”
 
Powering the SPAD revolution
Every digital camera, industrial vision system and scientific imaging instrument depends on image sensors to capture light and convert it into useful information. Over the decades, these sensors have improved, but they are now approaching the limits of how much information can be captured. The arrival of sensors based on single-photon avalanche diodes (SPADs) is changing that.
Unlike conventional image sensors, which essentially measure the intensity of light, SPAD sensors can precisely detect and time individual photons (the smallest units of light). This opens the door to an entirely new generation of imaging systems that can capture information that conventional cameras simply cannot see.
 
Singular Photonics is pioneering the development of SPAD-based image sensors that also integrate advanced on-chip computation. This allows information to be analysed at the point where light is first detected, making the company’s sensors capable of extracting meaningful information in real time. As sensors become increasingly capable of understanding the information they capture, they can enable smaller, faster and more efficient systems that meet the growing demands of edge computing and AI-driven applications.

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Link: https://www.sony-semicon.com/en/news/2026/2026081101.html

Sony Semiconductor Solutions and TSMC Agreed to Establish Joint Venture for Next-Generation Image Sensors

Atsugi, Japan and HSINCHU, Taiwan, R.O.C., August 11, 2026 - Sony Semiconductor Solutions Corporation (“Sony”) and Taiwan Semiconductor Manufacturing Company Limited (“TSMC”) (TWSE: 2330, NYSE: TSM) today announced the execution of a legally binding definitive agreement for the establishment of Advanced Vision Semiconductor Manufacturing Corporation as a joint venture (“JV”) in Koshi City, Kumamoto Prefecture, Japan. The JV will serve as a core hub for the development and manufacturing activities required for the volume production of image sensors for smartphones utilizing advanced manufacturing process technology. The JV is expected to commence volume production in 2029.

Sony will be the sole controlling shareholder and the JV is planned to operate as a consolidated subsidiary of Sony Group Corporation. The Representative Director of the JV is planned to be appointed by Sony.

Pursuant to the definitive agreement, Sony plans to contribute approximately 465 billion yen to the JV through a combination of cash contributions and the transfer of its assets* through a company split. TSMC plans to make cash contributions of approximately 282 billion yen. These capital contributions are expected to be made in phases based on market demand and other relevant business conditions. In addition to these capital contributions by Sony and TSMC, investments required to realize the production capacity planned by the JV are being considered on the premise that they would receive support from the Japanese government.

Under the strategic partnership, Sony intends to take a leading role in the development of core image sensor technologies, as well as product planning and product design. The JV plans to leverage TSMC’s advanced process technology and manufacturing expertise to drive development and manufacturing activities required for the volume production. Through this collaboration, the companies intend to accelerate the commercialization of image sensor products driven by customer needs while advancing technological innovation and strengthening manufacturing capacity.

The establishment of the JV and completion of the transaction are subject to the receipt of required regulatory approvals and the satisfaction of other customary closing conditions. 

All other aspects of the partnership remain unchanged from the announcement by Sony and TSMC titled “Sony Semiconductor Solutions and TSMC Enter Preliminary Agreement for Next-Generation Image Sensor Strategic Partnership” issued on May 8, 2026. 

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