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:this https URL.
View on arXiv@article{ding2025_2504.11326,
title={ PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild },
author={ Henghui Ding and Chang Liu and Nikhila Ravi and Shuting He and Yunchao Wei and Song Bai and Philip Torr and Kehuan Song and Xinglin Xie and Kexin Zhang and Licheng Jiao and Lingling Li and Shuyuan Yang and Xuqiang Cao and Linnan Zhao and Jiaxuan Zhao and Fang Liu and Mengjiao Wang and Junpei Zhang and Xu Liu and Yuting Yang and Mengru Ma and Hao Fang and Runmin Cong and Xiankai Lu and Zhiyang Chen and Wei Zhang and Tianming Liang and Haichao Jiang and Wei-Shi Zheng and Jian-Fang Hu and Haobo Yuan and Xiangtai Li and Tao Zhang and Lu Qi and Ming-Hsuan Yang },
journal={arXiv preprint arXiv:2504.11326},
year={ 2025 }
}