most citedPrompt-Aware Controllable Shadow Removal

4 citations · 4 across the 3 of their papers we have counts for

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cs.CV2026

Beyond the Single Camera: Agentic Multi-View Reasoning in Sports Video Understanding

Kerui Chen, Jinglu Wang, Xiaoyi Zhang +1

Recent Multimodal Large Language Models (MLLMs) achieve strong performance on single-view video understanding benchmarks. However, sports videos involve dense occlusion, rapid moti…

cs.CV2026

Scaling Video Understanding via Compact Latent Multi-Agent Collaboration

Kerui Chen, Jinglu Wang, Jianrong Zhang +3

Multi-modal large language models (MLLMs) advance vision language understanding but face inherent limitations in long-video tasks due to bounded perception context budgets. Existin…

cs.CV2025

ClusterStyle: Modeling Intra-Style Diversity with Prototypical Clustering for Stylized Motion Generation

Kerui Chen, Jianrong Zhang, Ming Li +2

Existing stylized motion generation models have shown their remarkable ability to understand specific style information from the style motion, and insert it into the content motion…

cs.CV2025

BVINet: Unlocking Blind Video Inpainting with Zero Annotations

Zhiliang Wu, Kerui Chen, Kun Li +2

Video inpainting aims to fill in corrupted regions of the video with plausible contents. Existing methods generally assume that the locations of corrupted regions are known, focusi…

cs.CV20254 cited

Prompt-Aware Controllable Shadow Removal

Kerui Chen, Zhiliang Wu, Wenjin Hou +3

Shadow removal aims to restore the image content in shadowed regions. While deep learning-based methods have shown promising results, they still face key challenges: 1) uncontrolle…