PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of
  Complex Videos in the Wild
This report provides a comprehensive overview of the 4th Pixel-level Video
Understanding in the Wild (PVUW) Challenge, held in conjunction with CVPR 2025.
It summarizes the challenge outcomes, participating methodologies, and future
research directions. The challenge features two tracks: MOSE, which focuses on
complex scene video object segmentation, and MeViS, which targets
motion-guided, language-based video segmentation. Both tracks introduce new,
more challenging datasets designed to better reflect real-world scenarios.
Through detailed evaluation and analysis, the challenge offers valuable
insights into the current state-of-the-art and emerging trends in complex video
segmentation. More information can be found on the workshop website:
https://pvuw.github.io/.
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Chang Liu
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Shuting He
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Yunchao Wei
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Song Bai
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Philip Torr
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Kehuan Song
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Xinglin Xie
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Kexin Zhang
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Licheng Jiao
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Lingling Li
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Shuyuan Yang
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Linnan Zhao
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Jiaxuan Zhao
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Fang Liu
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Junpei Zhang
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Xu Liu
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Yuting Yang
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Mengru Ma
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Hao Fang
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Runmin Cong
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Xiankai Lu
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Zhiyang Che
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Wei Zhan
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Tianming Liang
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Haichao Jiang
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Wei-Shi Zheng
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Jian-Fang Hu
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Haobo Yuan
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Xiangtai Li
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Xiangtai Li
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Tao Zhang
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Lu Qi
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Ming-Hsuan Yang
PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of
  Complex Videos in the Wild
This report provides a comprehensive overview of the 4th Pixel-level Video
Understanding in the Wild (PVUW) Challenge, held in conjunction with CVPR 2025.
It summarizes the challenge outcomes, participating methodologies, and future
research directions. The challenge features two tracks: MOSE, which focuses on
complex scene video object segmentation, and MeViS, which targets
motion-guided, language-based video segmentation. Both tracks introduce new,
more challenging datasets designed to better reflect real-world scenarios.
Through detailed evaluation and analysis, the challenge offers valuable
insights into the current state-of-the-art and emerging trends in complex video
segmentation. More information can be found on the workshop website:
https://pvuw.github.io/.
The PVUW Challenge provides insights into complex video segmentation by evaluating methodologies on challenging datasets in two tracks: MOSE and MeViS.
complex scene video object segmentation motion-guided language-based video segmentation