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SAMV-DUSt3R: Instance-Centric 3D Scene Decoupling from Sparse Multi-Views

arxiv.org/abs/2609.11279

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Updated 2 h ago · first seen 11 Sept 2026

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Published
11 Sept 2026
T1 · 2 h ago
arXiv
2609.11279
T1 · 2 h ago
Category
cs.CV
T1 · 2 h ago

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https://arxiv.org/abs/2609.11279currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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With the rising demand to decouple objects from 3D scenes, we propose SAMV-DUSt3R, an end-to-end model that injects SAM2 2D masks into MV-DUSt3R reconstruction. A Cross Flow Mask Block uses these masks to steer the network toward the target instance, jointly improving shape accuracy and achieving object-level disentanglement without multi-stage pipelines. To ensure reconstruction stability, a lightweight Spatial RankGNN selects the optimal reference view with a selection accuracy of 73.5\%. Extensive experiments demonstrate that our method boosts average reconstruction precision by 11\% across various metrics compared to state-of-the-art baselines. These results reveal a strong instance-disentanglement capability and clear benefits for driving, robotics, AR/VR, and heritage digitisation.currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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newcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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2609.11279currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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Langxu Zhao, Zuan Gu, Yingdan Zhang, Pengfei Zhao, Tianhan GaocurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.CVcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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https://arxiv.org/pdf/2609.11279currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.CVcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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11 Sept 2026currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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