AI RESEARCH
Robust Promptable Video Object Segmentation
arXiv CS.CV
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ArXi:2605.12006v1 Announce Type: new The performance of promptable video object segmentation (PVOS) models substantially degrades under input corruptions, which prevents PVOS deployment in safety-critical domains. This paper offers the first comprehensive study on robust PVOS (RobustPVOS). We first construct a new, comprehensive benchmark with two real-world evaluation datasets of 351 video clips and than 2,500 object masks under real-world adverse conditions. At the same time, we generate synthetic.