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/.

本研究解决了现有视频分割模型在复杂场景中表现不足的问题。我们引入了第六届大规模视频目标分割挑战，采用更具挑战性的MOSE、LVOS和MeViS数据集，评估视频对象分割（VOS）和指称视频对象分割（RVOS）。本次挑战吸引了来自20多个机构的129个团队参与，推动了视频目标分割技术的发展。

LSVOS挑战报告：大规模复杂和长视频目标分割