{"id":29009878,"url":"https://github.com/tencentarc/freesplatter","last_synced_at":"2025-06-25T15:33:35.200Z","repository":{"id":268486840,"uuid":"902141125","full_name":"TencentARC/FreeSplatter","owner":"TencentARC","description":"FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D 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align=\"center\"\u003e\n  \n# FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D Reconstruction\n\n\u003ca href='https://bluestyle97.github.io/projects/freesplatter/'\u003e\u003cimg src='https://img.shields.io/badge/Project_Page-Website-red?logo=googlechrome\u0026logoColor=white' alt='Project Page'\u003e\u003c/a\u003e\n\u003ca href=\"https://arxiv.org/abs/2412.09573\"\u003e\u003cimg src='https://img.shields.io/badge/arXiv-Paper-green?logo=arxiv\u0026logoColor=white' alt='arXiv'\u003e\u003c/a\u003e\n\u003ca href=\"https://huggingface.co/TencentARC/FreeSplatter\"\u003e\u003cimg src=\"https://img.shields.io/badge/%F0%9F%A4%97%20Model_Card-Huggingface-orange\"\u003e\u003c/a\u003e \n\u003ca href=\"https://huggingface.co/spaces/TencentARC/FreeSplatter\"\u003e\u003cimg src=\"https://img.shields.io/badge/%F0%9F%A4%97%20Gradio%20Demo-Huggingface-orange\"\u003e\u003c/a\u003e \u003cbr\u003e\n\n\u003c/div\u003e\n\n---\n\nThis repo is the official implementation of FreeSplatter, a feed-forward framework capable of generating high-quality 3D Gaussians from uncalibrated sparse-view images and recovering their camera parameters in mere seconds.\n\n\nhttps://github.com/user-attachments/assets/0c73b693-9428-46bd-843c-132434b9686f\n\n# ⚙️ Installation\n\nWe recommend using `Python\u003e=3.10`, `PyTorch\u003e=2.1.0`, and `CUDA\u003e=12.1`.\n```bash\nconda create --name freesplatter python=3.10\nconda activate freesplatter\npip install -U pip\n\n# Install PyTorch and xformers\n# You may need to install another xformers version if you use a different PyTorch version\npip install torch==2.4.0 torchvision==0.19.0 --index-url https://download.pytorch.org/whl/cu121\npip install xformers==0.0.27.post2\n\n# Install other requirements\npip install -r requirements.txt\n```\n\n# 🤖 Pretrained Models\n\nWe provide the following pretrained models:\n\n| Model | Description | #Params | Download |\n| --- | --- | --- | --- |\n| FreeSplatter-O | Object-level reconstruction model | 306M | [Download](https://huggingface.co/TencentARC/FreeSplatter/blob/main/freesplatter-object.safetensors) |\n| FreeSplatter-O-2dgs | Object-level reconstruction model using [2DGS](https://surfsplatting.github.io/) (finetuned from FreeSplatter-O) | 306M | [Download](https://huggingface.co/TencentARC/FreeSplatter/blob/main/freesplatter-object-2dgs.safetensors) |\n| FreeSplatter-S | Scene-level reconstruction model | 306M | [Download](https://huggingface.co/TencentARC/FreeSplatter/blob/main/freesplatter-scene.safetensors) |\n\n# 💫 Inference\n\nWe recommand to start a gradio demo in your local machine, simply run:\n```bash\npython app.py\n```\n\n# ⚖️ License\n\nFreeSplatter's code and models are licensed under the [Apache 2.0 License](LICENSE.txt) with additional restrictions to comply with Tencent's open-source policies. Besides, the libraries [Hunyuan3D-1](https://github.com/Tencent/Hunyuan3D-1) and [BRIAAI RMBG-2.0](https://huggingface.co/briaai/RMBG-2.0) have their own non-commercial licenses.\n\n# :books: Citation\n\nIf you find our work useful for your research or applications, please cite using this BibTeX:\n\n```BibTeX\n@article{xu2024freesplatter,\n  title={FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D Reconstruction},\n  author={Xu, Jiale and Gao, Shenghua and Shan, Ying},\n  journal={arXiv preprint arXiv:2412.09573},\n  year={2024}\n}\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftencentarc%2Ffreesplatter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftencentarc%2Ffreesplatter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftencentarc%2Ffreesplatter/lists"}