2026 WACV WACV 2026

Sun-E: Dataset and Benchmark for Event-Based Sun Sensing

Abstract

Event cameras are increasingly being explored for space applications due to their high dynamic range and increased spatiotemporal resolution. Existing datasets in this application have focused on capturing low-light, sub-pixel space objects and Earth observation scenarios. There remains a notable gap in datasets tailored to high-illumination conditions, particularly those involving direct solar imaging. This work introduces a dataset of solar event recordings captured with an event camera in a controlled sun-simulator environment. The dataset is specifically designed to support research in sun sensing and stray light analysis for spacecraft attitude estimation applications. It includes raw event data, annotated sun centroid locations, object motion profiles, and secondary optical aberration artifacts. In addition to the dataset, we present a systematic methodology for estimating the sun vector, intended to serve as a benchmark for evaluating sun sensing approaches in this application. All data and code are open source to facilitate further study.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Science and Computer Vision and Machine Learning
🧭 Keyword Pioneer — sun sensing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio