Matrix-3D - Kunlun Wanwei's open-source 3D world model
Matrix-3D is a framework developed by Kunlun Tech's Skywork AI team for generating explorable panoramic 3D worlds. The framework combines panoramic video generation with 3D reconstruction, starting from single images or text cues to generate high-quality, omnidirectional...
What is Matrix-3D?
Matrix-3D is a framework developed by the Skywork AI team at Kunlun Tech for generating explorable panoramic 3D worlds. Combining panoramic video generation and 3D reconstruction, the framework generates high-quality, omnidirectional, explorable 3D scenes starting from a single image or text prompt. Based on a trajectory-guided panoramic video diffusion model and two 3D reconstruction methods (fast feedforward network and high-quality optimization method), Matrix-3D achieves large-scale, highly consistent 3D scene generation, supports text and image input, and possesses high efficiency and strong generalization capabilities. The accompanying Matrix-Pano dataset provides strong support for research.
Main functions of Matrix-3D
- Panoramic video generationGenerates high-quality panoramic videos from single images or text prompts, and supports user-defined camera paths.
- 3D scene reconstructionIt offers two 3D reconstruction methods: fast feedforward networks and high-quality optimization methods, to meet different needs.
- Multiple input supportIt supports text and image input, allowing users to select according to their needs and generate corresponding 3D scenes.
- Large-scale scene generationThe generated 3D scene has a large range and supports 360° free exploration, which is superior to other methods.
- High controllabilityUsers can customize the generated trajectory and infinitely continue and expand upon the generated scene.
The technical principles of Matrix-3D
- Track-guided panoramic video generationA video diffusion model is trained using a scene mesh rendering map as conditional input. The model generates panoramic video based on user-defined camera trajectories, ensuring spatial consistency and geometric accuracy of the generated content.
- Conversion of panoramic video to 3D sceneBased on the Transformer architecture, it directly predicts 3D geometric properties from the latent features of the generated panoramic video. This enables fast 3D scene reconstruction, suitable for real-time applications.
- Optimization-based methodsThis feature performs super-resolution processing and 3D Gaussian Splatting optimization on the generated panoramic video. It produces high-quality, richly detailed 3D scenes, suitable for scenarios with high visual quality requirements.
- Matrix-Pano datasetTo address the scarcity of existing 3D scene data, Matrix-3D provides a large-scale synthetic dataset. It contains 116,759 high-quality static panoramic video sequences, each with camera tracking and annotations. The diversity and high quality of the dataset provide strong support for model training.
- Panoramic representationUsing panoramic images as an intermediate representation, covering a 360° horizontal view and a 180° vertical view, a panoramic video is generated by stitching together panoramic images from multiple locations, containing all the information needed to generate the 3D world.
Project address of Matrix-3D
- Project official websitehttps://matrix-3d.github.io/
- GitHub repositoryhttps://github.com/SkyworkAI/Matrix-3D
- HuggingFace model libraryhttps://huggingface.co/Skywork/Matrix-3D
- Technical Papers: https://github.com/SkyworkAI/Matrix-3D/blob/main/asset/report.pdf
Applications of Matrix-3D
- Game developmentIt can quickly generate high-quality 3D game scenes, shorten the development cycle, and enhance the personalized experience for players.
- Film and television productionGenerate realistic virtual scenes and effects, reduce shooting costs, and assist in storyboard design and scene preview.
- Virtual Reality (VR) and Augmented Reality (AR)Matrix-3D generates panoramic 3D scenes that support 360° free exploration, which can be used in virtual tourism and AR applications to enhance immersion.
- Robot navigation and autonomous drivingGenerate complex 3D environments for use in training and testing robot navigation and autonomous driving systems, improving decision-making safety.
- Education and TrainingGenerate virtual labs and realistic training scenarios for use in education and skills training to improve effectiveness.