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LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation

9 September 2024
Henghui Ding
Lingyi Hong
Chang Liu
Ning Xu
L. Yang
Yuchen Fan
Deshui Miao
Yameng Gu
Xin Li
Zhenyu He
Yaowei Wang
Ming-Hsuan Yang
Jinming Chai
Qin Ma
Junpei Zhang
Licheng Jiao
Fang Liu
Xinyu Liu
Jing Zhang
Kexin Zhang
Xu Liu
Lingling Li
Hao Fang
Feiyu Pan
Xiankai Lu
Wei Zhang
Runmin Cong
Tuyen Tran
Bin Cao
Yisi Zhang
Hanyi Wang
Xingjian He
Jing Liu
    VOS
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Abstract

Despite the promising performance of current video segmentation models on existing benchmarks, these models still struggle with complex scenes. In this paper, we introduce the 6th Large-scale Video Object Segmentation (LSVOS) challenge in conjunction with ECCV 2024 workshop. This year's challenge includes two tasks: Video Object Segmentation (VOS) and Referring Video Object Segmentation (RVOS). In this year, we replace the classic YouTube-VOS and YouTube-RVOS benchmark with latest datasets MOSE, LVOS, and MeViS to assess VOS under more challenging complex environments. This year's challenge attracted 129 registered teams from more than 20 institutes across over 8 countries. This report include the challenge and dataset introduction, and the methods used by top 7 teams in two tracks. More details can be found in our homepage https://lsvos.github.io/.

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