THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation

• URL: http://arxiv.org/abs/2506.06748v1
• Date: Sat, 07 Jun 2025 10:33:16 GMT
• Title: THU-Warwick Submission for EPIC-KITCHEN Challenge 2025: Semi-Supervised Video Object Segmentation
• Authors: Mingqi Gao, Haoran Duan, Tianlu Zhang, Jungong Han,
• Abstract summary: Our method combines large-scale visual pretraining from SAM2 with depth-based geometric cues to handle complex scenes and long-term tracking.<n>On the VISOR test set, our method reaches a J&F score of 90.1%.
• Score: 49.54727231738117
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this report, we describe our approach to egocentric video object segmentation. Our method combines large-scale visual pretraining from SAM2 with depth-based geometric cues to handle complex scenes and long-term tracking. By integrating these signals in a unified framework, we achieve strong segmentation performance. On the VISOR test set, our method reaches a J&F score of 90.1%.

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