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
