mlsanityData to 14 Oct 2026

CSS-Segment: 2nd Place Report of LSVOS Challenge VOS Track

arXiv 2408.13582 ↗First posted 24 Aug 2024cs.CVcited by 0

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Abstract (arXiv)

Video object segmentation is a challenging task that serves as the cornerstone of numerous downstream applications, including video editing and autonomous driving. In this technical report, we briefly introduce the solution of our team "yuanjie" for video object segmentation in the 6-th LSVOS Challenge VOS Track at ECCV 2024. We believe that our proposed CSS-Segment will perform better in videos of complex object motion and long-term presentation. In this report, we successfully validated the effectiveness of the CSS-Segment in video object segmentation. Finally, our method achieved a J&F score of 80.84 in and test phases, and ultimately ranked 2nd in the 6-th LSVOS Challenge VOS Track at ECCV 2024.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 7 references that are in the map. First posted on arXiv 24 Aug 2024.

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References · 3

  1. 2023MOSE: A New Dataset for Video Object Segmentation in Complex Scenescited by 234
  2. 2023MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressionscited by 228
  3. 2024LVOS: A Benchmark for Large-scale Long-term Video Object Segmentationcited by 44

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