FracGen: Learning How Objects Stretch and Tear with Physics-Informed Video Generation

arXiv:2609.38152 · cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Project page: https://fracgen.github.io

Terminology

• Consistency — 16× in this paper · explained in 3 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Material Point Method — 8× in this paper
• Ablation — 7× in this paper · explained in 1 episode
• Fidelity — 5× in this paper · explained in 2 episodes
• ACM Transactions on Graphics — 4× in this paper
• Ablation Studies — 4× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Gaussian Splatting — 4× in this paper · explained in 4 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• 3D Gaussian Splatting — 3× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 3 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Latent Space — 3× in this paper · explained in 7 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• 3D Gaussian Splatting (3DGS) — 2× in this paper · explained in 4 episodes
• Damage Progression Alignment — 2× in this paper
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Optical Flow — 2× in this paper · explained in 2 episodes
• Stretching Axis Coherence — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Angular Error — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• VideoPhy: Evaluating Physical Commonsense for Video Generation
• PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation
• 4DNeX: Feed-Forward 4D Generative Modeling Made Easy
• Objaverse: A Universe of Annotated 3D Objects
• Generative Models: What Do They Know? Do They Know Things? Let's Find Out!
• Segment Anything
• CoWTracker: Tracking by Warping instead of Correlation
• Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion
• Wan: Open and Advanced Large-Scale Video Generative Models
• Think Before You Diffuse: Infusing Physical Rules into Video Diffusion
• Neural Stress Fields for Reduced-order Elastoplasticity and Fracture

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models