arXiv · 2609.06078
Report of the 8th LSVOS Challenge: Complex and Multimodal Video Object Segmentation
Abstract
This report summarizes the 8th Large-scale Video Object Segmentation (LSVOS) Challenge, held in conjunction with ECCV 2026. The challenge evaluates video segmentation in three complementary settings: complex semi-supervised video object segmentation on MOSEv2, text-guided referring video object segmentation on MeViSv2-Text, and audio-guided referring video object segmentation on MeViSv2-Audio. We describe the tasks and evaluation protocols and review the methods of the top three teams in each track. Across the nine leading solutions, foundation segmentation models are combined with target-aware memory, multimodal reasoning, explicit target-existence verification, agentic interaction, and corrective tracking. These systems illustrate a broader transition from single-model mask propagation toward modular pipelines that reason about object identity, query validity, and temporal reliability.
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Chang Liu, Henghui Ding, Lingyi Hong, Ning Xu, Linjie Yang, Yuchen Fan, Canyang Wu, Jinrong Zhang, Xusheng He, Ce Bian, Xianjing Han, Jianlong Wu, Mingqi Gao, Sijie Li, Jungong Han, JeongRae Kim, Chaehyun Kim, Changwon Lim, Jungyoon Lee, Gyuil Lim, Doeon Kim, Seong-heum Kim, Pranjal Aggarwal, Sean Welleck, Yiwen Ren, Jianing Liu, Yingxin Wang, Kexin Zhang, Licheng Jiao, Lingling Li, Xu Liu, Jinxing Zhou, Suiyi Zhao, Yanghao Zhou, Ruohao Guo, Liangtao Shi, Jinxia Xie, Xiantao Hu, Ting Liu. 2026-09-05. Report of the 8th LSVOS Challenge: Complex and Multimodal Video Object Segmentation. https://arxiv.org/abs/2609.06078
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