Re-Prompting SAM 3 via Object Retrieval: 3rd of the 5th PVUW MOSE Track

• URL: http://arxiv.org/abs/2603.23788v1
• Date: Tue, 24 Mar 2026 23:45:15 GMT
• Title: Re-Prompting SAM 3 via Object Retrieval: 3rd of the 5th PVUW MOSE Track
• Abstract summary: We develop an automatic re-prompting framework to improve robustness under target disappearance and reappearance.<n>Our solution achieves a J&F of 51.17% on the test set, ranking 3rd in the MOSEv2 track.
• Score: 51.15679610275694
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This technical report explores the MOSEv2 track of the PVUW 2026 Challenge, which targets complex semi-supervised video object segmentation. Built on SAM~3, we develop an automatic re-prompting framework to improve robustness under target disappearance and reappearance, severe transformation, and strong same-category distractors. Our method first applies the SAM~3 detector to later frames to identify same-category object candidates, and then performs DINOv3-based object-level matching with a transformation-aware target feature pool to retrieve reliable target anchors. These anchors are injected back into the SAM~3 tracker together with the first-frame mask, enabling multi-anchor propagation rather than relying solely on the initial prompt. This simple directly benefits several core challenges of MOSEv2. Our solution achieves a J&F of 51.17% on the test set, ranking 3rd in the MOSEv2 track.

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