Initial release

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README.md

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+---
+license: mit
+pipeline_tag: image-to-3d
+tags:
+- 3d-reconstruction
+- 3d-modeling
+- triposf
+- vae
+---
+# TripoSF: High-Resolution 3D Shape Modeling with SparseFlex
+
+TripoSF is a state-of-the-art 3D shape modeling framework that enables differentiable mesh reconstruction at resolutions up to $1024^3$ directly from rendering losses. This repository contains the pretrained VAE model for high-fidelity 3D reconstruction.
+
+## Model Description
+
+TripoSF leverages a novel SparseFlex representation that combines the accuracy of Flexicubes with an efficient sparse voxel structure, focusing computation on surface-adjacent regions.
+
+### Key Features
+- 🔍 Ultra-high resolution reconstruction (up to $1024^3$)
+- 🎯 Direct optimization from rendering losses
+- 🌐 Natural handling of open surfaces and complex topologies
+- 💾 Memory-efficient sparse computation
+- 🔄 Differentiable mesh extraction with sharp features
+
+## Intended Uses
+
+This model is designed for:
+- High-fidelity 3D shape reconstruction
+- Mesh generation and modeling
+- 3D asset creation and optimization
+
+## Requirements
+
+- CUDA-capable GPU (≥12GB VRAM recommended for $1024^3$ resolution)
+- PyTorch 2.0+
+
+## Usage
+
+For detailed usage instructions, please visit our [GitHub repository](https://github.com/VAST-AI-Research/TripoSF).
+
+## About
+
+TripoSF 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:
+- [Project Page](https://xianglonghe.github.io/TripoSF/)
+- [Paper](https://arxiv.org/)
+- [GitHub Repository](https://github.com/VAST-AI-Research/TripoSF)

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