Cast and Attached Shadow Detection via Iterative Light and Geometry Reasoning

ArXi:2512.06179v2 Announce Type: replace Shadows encode rich information about scene geometry and illumination, yet existing methods either predict a unified shadow mask or overlook attached shadows entirely. We address this gap by proposing a framework for jointly detecting cast and attached shadows through explicit physical modeling of light direction and surface geometry. Our approach is grounded in a simple observation: surfaces facing away from the light source tend to fall into shadow.