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arXiv Computer Vision By Jiamin Xu, Cong Wang, Zheng Dong, Chi Wang, Renshu Gu, Weiwei Xu, Gang Xu

WildShadowRemover: In-the-Wild Video Shadow Removal via Detail-Preserving Video Diffusion Models

Read the original on arXiv Computer Vision →

WildShadowRemover is a framework that adapts a pretrained video diffusion model for robust in-the-wild video shadow removal using LoRA fine-tuning. It augments the frozen VAE decoder with a detail injection module and introduces a shadow‑mask‑guided frequency‑decomposed modulation module to restore high‑frequency textures while suppressing shadow artifacts, with monocular depth priors providing geometry‑aware guidance. The authors also create WildShadow, a large‑scale paired video shadow removal dataset, and show that their method outperforms existing approaches in shadow removal quality, temporal consistency, and generalization across challenging real‑world scenarios.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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