AI RESEARCH
VAD4Space: Visual Anomaly Detection for Planetary Surface Imagery
arXiv CS.AI
•
ArXi:2603.13993v1 Announce Type: cross Space missions generate massive volumes of high-resolution orbital and surface imagery that far exceed the capacity for manual inspection. Detecting rare phenomena is scientifically critical, yet traditional supervised learning struggles due to scarce labeled examples and closed-world assumptions that prevent discovery of genuinely novel observations. In this work, we investigate Visual Anomaly Detection (VAD) as a framework for automated discovery in planetary exploration.