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/.

翻译：尽管当前视频分割模型在现有基准测试中表现出色，但这些模型在复杂场景中仍面临困难。本文介绍了与ECCV 2024研讨会联合举办的第六届大规模视频目标分割（LSVOS）挑战赛。本届挑战赛包含两个任务：视频目标分割（VOS）与指代视频目标分割（RVOS）。今年我们采用最新数据集MOSE、LVOS和MeViS取代经典的YouTube-VOS与YouTube-RVOS基准，以评估模型在更具挑战性的复杂环境下的VOS性能。本届挑战赛吸引了来自8个国家、20余所机构的129支注册团队。本报告涵盖挑战赛与数据集介绍，以及两个赛道前7名团队采用的方法。更多细节请访问我们的主页https://lsvos.github.io/。