MomentSeg: Moment-Centric Sampling for Enhanced Video Pixel Understanding

• URL: http://arxiv.org/abs/2510.09274v1
• Date: Fri, 10 Oct 2025 11:18:21 GMT
• Title: MomentSeg: Moment-Centric Sampling for Enhanced Video Pixel Understanding
• Authors: Ming Dai, Sen Yang, Boqiang Duan, Wankou Yang, Jingdong Wang,
• Abstract summary: Referring Video Object (RefVOS) seeks to segment target objects in videos guided by natural language descriptions.<n>We propose a unified framework that jointly optimize Temporal Sentence Grounding (TSG) and RefVOS, naturally incorporating key moment grounding capability.
• Score: 40.37010049965347
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Referring Video Object Segmentation (RefVOS) seeks to segment target objects in videos guided by natural language descriptions, demanding both temporal reasoning and fine-grained visual comprehension. Existing sampling strategies for LLM-based approaches typically rely on either handcrafted heuristics or external keyframe models. The former often overlooks essential temporal cues, while the latter increases system complexity. To address this, we propose a unified framework that jointly optimizes Temporal Sentence Grounding (TSG) and RefVOS, naturally incorporating key moment grounding capability. During training, we introduce a novel TSG paradigm that employs a dedicated \texttt{[FIND]} token for key moment identification through temporal token similarity matching, thereby avoiding the need for external timestamp encodings. For inference, we design a Moment-Centric Sampling (MCS) strategy that densely samples informative moments while sparsely sampling non-essential frames, preserving both motion details and global context. To further enhance tracking stability, we develop Bidirectional Anchor-updated Propagation (BAP), which leverages the most relevant moment as start point for high-quality mask initialization and dynamically updates at sampled points to mitigate accumulated errors. Code and model will be available at: https://github.com/Dmmm1997/MomentSeg

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