SaSaSaSa2VA: 2nd Place of the 5th PVUW MeViS-Text Track
arXiv cs.CV / 3/31/2026
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Key Points
- The paper SaSaSaSa2VA targets referring video object segmentation (RVOS), arguing that existing approaches rely too heavily on static textual cues and thus extend the setting toward motion-centric expressions.
- It builds on Sa2VA by increasing input frames and using [SEG] tokens, then adds a simple target existence-aware verification mechanism inspired by the need to verify whether targets exist before/while segmenting.
- The authors report a final score of 89.19 at the 5th PVUW Challenge (MeViS-Text Track), where the method won 2nd place.
- Quantitative results and ablation studies indicate that the existence-aware verification strategy is sufficient to unlock strong performance specifically on motion-centric referring tasks.
- The work positions MeViS benchmark improvements (referring & reasoning motion expressions plus no-target queries) as a key testbed for evaluating robustness beyond text-only grounding.
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