VOS-Agent: The 1st Place Solution for the 8th LSVOS Challenge (MOSEv2 Track)

VOS-Agent, a collaborative framework built on SAM3, won first place in the MOSEv2 Track of the 8th LSVOS Challenge at ECCV 2026, achieving 69.82% on the official J&F metric. The framework uses a Target Perception and Routing Agent to assign sequences to regular, tiny, or semantic-dominated routes, with specialized agents for tiny and semantic-dominated targets.

arXiv:2608.12721v1 Announce Type: new Abstract: Complex video object segmentation requires robust target propagation under severe occlusion, disappearance and reappearance. Although SAM3 provides strong promptable mask propagation, a uniform inference path remains unreliable for tiny targets with insufficient visual evidence and semantic-dominated targets whose identities depend on explicit attributes. To this end, we present VOS-Agent, a collaborative framework that retains SAM3 as the shared dense segmentation module and conditionally activates specialized agents according to target characteristics. A Target Perception and Routing Agent assigns each sequence to a regular, tiny, or semantic-dominated route. Tiny targets are supported by a Visual Tracking Agent through confidence-aware box prompts, while semantic-dominated targets are handled by an MLLM-based Semantic Agent through description-guided localization and candidate verification. On the MOSEv2 test set, VOS-Agent achieves 69.82% on the official $\mathcal{J}\&\dot{\mathcal{F}}$ metric and ranks first in the MOSEv2 Track of the 8th LSVOS Challenge at ECCV 2026.