TripoSG

--- license: mit pipeline_tag: image-to-3d tags: - triposg - 3d-generation - rectified-flow --- # TripoSG - High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models TripoSG is a state-of-the-art image-to-3D generation foundation model that leverages large-scale rectified flow transformers to produce high-fidelity 3D shapes from single images. ## Model Description ### Model Architecture TripoSG utilizes a novel architecture combining: - Rectified Flow (RF) based Transformer for stable, linear trajectory modeling - Advanced VAE with SDF-based representation and hybrid geometric supervision - Cross-attention mechanism for image feature condition - 1.5B parameters operating on 2048 latent tokens ## Intended Uses This model is designed for: - Converting single images to high-quality 3D meshes - Creative and design applications - Gaming and VFX asset creation - Prototyping and visualization ## Requirements - CUDA-capable GPU (>8GB VRAM) ## Usage For detailed usage instructions, please visit our [GitHub repository](https://github.com/VAST-AI-Research/TripoSG). ## About TripoSG is developed by [Tripo](https://www.tripo3d.ai), [VAST AI Research](https://github.com/orgs/VAST-AI-Research), pushing the boundaries of 3D Generative AI. For more information: - [GitHub Repository](https://github.com/VAST-AI-Research/TripoSG) - [Paper](https://arxiv.org/abs/2502.06608) - [Gradio Demo](https://huggingface.co/spaces/VAST-AI/TripoSG)

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