PhysX-Omni unifies simulation-ready 3D asset generation across rigid, deformable, and articulated objects via a new geometry representation, the PhysXVerse dataset, and the PhysX-Bench evaluation suite.
Urdf-anything: Constructing articulated objects with 3d multimodal language model
4 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
GraspFoM creates a shared 3D latent from SAM3D priors, adds an anchor-initialized diffuser for multimodal grasps, and uses reconstruction-aware scoring plus residual updates to jointly achieve SOTA reconstruction and grasping with few extra parameters.
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.
The paper surveys 3D generation techniques for embodied AI and robotics, categorizing them into data generation, simulation environments, and sim-to-real bridging while identifying bottlenecks in physical validity and transfer.
citing papers explorer
-
PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects
PhysX-Omni unifies simulation-ready 3D asset generation across rigid, deformable, and articulated objects via a new geometry representation, the PhysXVerse dataset, and the PhysX-Bench evaluation suite.
-
GraspFoM: Towards Reconstruction-Driven Robotic Grasping with 3D Foundation Priors
GraspFoM creates a shared 3D latent from SAM3D priors, adds an anchor-initialized diffuser for multimodal grasps, and uses reconstruction-aware scoring plus residual updates to jointly achieve SOTA reconstruction and grasping with few extra parameters.
-
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.
-
3D Generation for Embodied AI and Robotic Simulation: A Survey
The paper surveys 3D generation techniques for embodied AI and robotics, categorizing them into data generation, simulation environments, and sim-to-real bridging while identifying bottlenecks in physical validity and transfer.