Remove shadows in images using weak supervision with UnShadowNet

Remove shadows in images using weak supervision with UnShadowNet

UnShadowNet: Illumination Critic Guided Contrastive Learning For Shadow Removal

arXiv paper abstract https://arxiv.org/abs/2203.15441v1

arXiv PDF paper https://arxiv.org/pdf/2203.15441v1.pdf

Shadows are frequently encountered natural phenomena that significantly hinder the performance of computer vision perception systems in practical settings, e.g., autonomous driving.

... eliminate shadow ... requires pairs of aligned shadowed and non-shadowed images which are difficult to obtain.

... introduce a novel weakly supervised shadow removal framework UnShadowNet trained using contrastive learning.

... comprises of a DeShadower network responsible for removal of the extracted shadow under the guidance of an Illumination network which is trained adversarially by the illumination critic and a Refinement network to further remove artifacts.

... UnShadowNet can ... be ... extended to a fully-supervised setup to exploit the ground-truth when available.

UnShadowNet outperforms ... state-of-the-art ... on three publicly available shadow datasets ... in both the weakly and fully supervised setups.

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