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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
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
Networking Coffee Break
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.
Networking Lunch Break
Session 2: Breaking the Performance Limits of CMOS Image Sensors
Colloidal Quantum-dot Based SWIR Image Sensing Technologies
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
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
Networking Coffee Break
Session 3: Robotics & Automotive Vision - Building Eyes for Intelligent Machines
Topic to be confirmed
Speaker TBC
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
Drink Reception
End of Day One
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
Networking Lunch Break
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
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
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
From Embodied AI to Autonomous Driving — How Global Shutter Vision Sensors Empower Every Scene
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
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
End of Conference