Shadow removal aims at restoring the image content within shadow regions, pursuing a
uniform distribution of illumination that is consistent between shadow and non-shadow …

In this paper we present S3R-Net the Self-Supervised Shadow Removal Network. The two-
branch WGAN model achieves self-supervision relying on the unify-and-adapt phenomenon …

Shadow-affected images often exhibit pronounced spatial discrepancies in color and
illumination, consequently degrading various vision applications including object detection …

Video Shadow Detection (VSD) is an important computer vision task focusing on detecting
and segmenting shadows throughout the entire video sequence. Despite their remarkable …

Shadows are formed when light encounters obstacles, leading to areas of diminished
illumination. In computer vision, shadow detection, removal, and generation are crucial for …

Recent advancements in deep learning have yielded promising results for the image
shadow removal task. However, most existing methods rely on binary pre-generated …

Shadow, as a natural consequence of light interacting with objects, plays a crucial role in
shaping the aesthetics of an image, which however also impairs the content visibility and …