RecGen achieves state-of-the-art 3D multi-object scene reconstruction from sparse RGB-D views by combining compositional synthetic scene generation with strong 3D shape priors, outperforming SAM3D by 30%+ in shape quality and pose accuracy while using 80% fewer meshes.
Artvip: Articulated digital assets of visual realism, modular interaction, and physical fidelity for robot learning
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Artiverse is a new dataset of 5.4K human-authored articulated 3D objects with detailed annotations for parts, multi-DoF joints, interior structures, and physical attributes to enable functional modeling and physics-based interaction.
A simulator-in-the-loop multi-modal method refines physical properties of incomplete 3D articulated objects to improve simulation stability and downstream robot policy performance.
citing papers explorer
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Reconstruction by Generation: 3D Multi-Object Scene Reconstruction from Sparse Observations
RecGen achieves state-of-the-art 3D multi-object scene reconstruction from sparse RGB-D views by combining compositional synthetic scene generation with strong 3D shape priors, outperforming SAM3D by 30%+ in shape quality and pose accuracy while using 80% fewer meshes.
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Artiverse: A Diverse and Physically Grounded Dataset for Articulated Objects
Artiverse is a new dataset of 5.4K human-authored articulated 3D objects with detailed annotations for parts, multi-DoF joints, interior structures, and physical attributes to enable functional modeling and physics-based interaction.
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Automatically Improving Simulation Physics for Articulated Objects
A simulator-in-the-loop multi-modal method refines physical properties of incomplete 3D articulated objects to improve simulation stability and downstream robot policy performance.