The workshop explores the joint optimization of sensors and machine learning models, pushing beyond traditional paradigms of data acquisition and processing. We aim to rethink the foundations of how machines sense the world by replacing hand-crafted ISPs, leveraging learnable sensor layouts, and adopting task-driven sensing strategies.

We welcome original contributions and position papers in the following topics (non-exhaustive):

• Sensor optimization for e.g. computer vision (bit-depth, pixel layouts, color filter design)

• RAW-to-task or RAW-to-label approaches for visual tasks

• Co-design of neural networks and sensor hardware

• Low-bit and energy-efficient sensing for embedded or mobile devices

• Benchmarks, datasets, and metrics for evaluating sensor-model pipelines

• Generalization and robustness of sensor-model systems in real-world conditions

• Failure case studies and negative results in joint optimization pipelines

Join us to engage with cutting-edge research and cross-disciplinary discussions that are shaping the future of sensor systems for real-world deployment across mobile, embedded, and autonomous platforms.

• Submission Deadline: August 22, 2025

• Review Period & Oral Decisions: August 23 – September 17, 2025

• Notification of Acceptance: September 22, 2025

• Camera-Ready Deadline: October 15, 2025

• Workshop Date: December 6 or 7, 2025

Coming Soon 

Please visit the Call for papers page for detailed guidelines.

Call for Reviewers

If you are interested in contributing to our paper review process, please write contact us at l2s-workshop@googlegroups.com. We will publicly acknowledge our program committee members. Your expertise and time dedicated to this effort are greatly appreciated and crucial to the success of the workshop.