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.
SceneComplete: Open-World 3D Scene Completion in Complex Real World Environments for Robot Manipulation
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Empirical study finds that object pose and shape estimation followed by antipodal grasp sampling outperforms end-to-end grasp synthesis for 7-DoF parallel-jaw grasping from single-view RGB-D input.
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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Object Pose and Shape Estimation for Grasping: Does it Work?
Empirical study finds that object pose and shape estimation followed by antipodal grasp sampling outperforms end-to-end grasp synthesis for 7-DoF parallel-jaw grasping from single-view RGB-D input.