ReconPhys is the first feedforward neural network that jointly reconstructs 3D geometry and appearance via Gaussian Splatting while estimating physical attributes from a single monocular video using self-supervised training.
Omniphysgs: 3d constitutive gaussians for general physics-based dynamics generation
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
MoSA learns residual stress operators on an isotropic backbone using a physics-informed cascaded network and motion constraints to capture mild anisotropy and heterogeneity for improved real-to-sim dynamics.
PhysMorph-GS injects visual supervision via deformation gradients in differentiable physics simulation and uses phased Chamfer-guided plasticity to reduce silhouette error by up to 49.9% compared to physics-only baselines.
A feed-forward video latent transformer that predicts time-varying 3D Gaussian primitives from one image to produce controllable 4D scenes with appearance, geometry, and motion.
citing papers explorer
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ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video
ReconPhys is the first feedforward neural network that jointly reconstructs 3D geometry and appearance via Gaussian Splatting while estimating physical attributes from a single monocular video using self-supervised training.
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MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual Anisotropy
MoSA learns residual stress operators on an isotropic backbone using a physics-informed cascaded network and motion constraints to capture mild anisotropy and heterogeneity for improved real-to-sim dynamics.
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PhysMorph-GS: Render-Guided Volumetric Morphing with Differentiable Physics
PhysMorph-GS injects visual supervision via deformation gradients in differentiable physics simulation and uses phased Chamfer-guided plasticity to reduce silhouette error by up to 49.9% compared to physics-only baselines.
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Diff4Splat: Controllable 4D Scene Generation with Latent Dynamic Reconstruction Models
A feed-forward video latent transformer that predicts time-varying 3D Gaussian primitives from one image to produce controllable 4D scenes with appearance, geometry, and motion.