PhysGen: Rigid-Body Physics-Grounded Image-to-Video Generation
PhysGen is a novel method for generating realistic videos from a single image using physical simulation and data-driven techniques, developed by researchers from the University of Illinois and Apple.
Read original article
PhysGen is a new method for generating videos from a single image and specific input conditions, such as applied forces and torques. Developed by researchers from the University of Illinois Urbana-Champaign and Apple, this approach combines model-based physical simulation with data-driven video generation to create realistic and temporally consistent videos. The system comprises three main components: an image understanding module that captures the image's geometry, materials, and physical parameters; a dynamics simulation module that applies rigid-body physics to simulate realistic motion; and a rendering module that uses generative video diffusion to produce high-quality video footage. The videos generated by PhysGen are not only visually realistic but also allow for precise control over the dynamics, outperforming existing image-to-video generation methods in both quantitative assessments and user studies. The framework's interleaved components work together to interpret the image's semantics, simulate physical interactions, and render the final video output, making it suitable for various applications, including creating animations from images and enabling user interaction with dynamic content. The research will be presented at the European Conference on Computer Vision (ECCV) in 2024.
Related
Meta 3D Gen
Meta introduces Meta 3D Gen (3DGen), a fast text-to-3D asset tool with high prompt fidelity and PBR support. It integrates AssetGen and TextureGen components, outperforming industry baselines in speed and quality.
Physics-Based Deep Learning Book
The Physics-based Deep Learning Book (v0.2) introduces deep learning for physical simulations, covering topics like physical loss constraints, tailored training algorithms, and uncertainty modeling. It includes Jupyter notebooks for practical learning.
New framework allows robots to learn via online human demonstration videos
Researchers develop a framework for robots to learn manipulation skills from online human demonstration videos. The method includes Real2Sim, Learn@Sim, and Sim2Real components, successfully training robots in tasks like tying knots.
Diffusion Texture Painting
Researchers introduce Diffusion Texture Painting, a method using generative models for interactive texture painting on 3D meshes. Artists can paint with complex textures and transition seamlessly. The innovative approach aims to inspire generative model exploration.
Tuning-Free Personalized Image Generation
Meta AI has launched the "Imagine yourself" model for personalized image generation, improving identity preservation, visual quality, and text alignment, while addressing limitations of previous techniques through innovative strategies.
0 commentsRelated
Meta 3D Gen
Meta introduces Meta 3D Gen (3DGen), a fast text-to-3D asset tool with high prompt fidelity and PBR support. It integrates AssetGen and TextureGen components, outperforming industry baselines in speed and quality.
Physics-Based Deep Learning Book
The Physics-based Deep Learning Book (v0.2) introduces deep learning for physical simulations, covering topics like physical loss constraints, tailored training algorithms, and uncertainty modeling. It includes Jupyter notebooks for practical learning.
New framework allows robots to learn via online human demonstration videos
Researchers develop a framework for robots to learn manipulation skills from online human demonstration videos. The method includes Real2Sim, Learn@Sim, and Sim2Real components, successfully training robots in tasks like tying knots.
Diffusion Texture Painting
Researchers introduce Diffusion Texture Painting, a method using generative models for interactive texture painting on 3D meshes. Artists can paint with complex textures and transition seamlessly. The innovative approach aims to inspire generative model exploration.
Tuning-Free Personalized Image Generation
Meta AI has launched the "Imagine yourself" model for personalized image generation, improving identity preservation, visual quality, and text alignment, while addressing limitations of previous techniques through innovative strategies.