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--- |
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pipeline_tag: image-to-3d |
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license: apache-2.0 |
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--- |
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# GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction |
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This repository provides the reconstructed meshes and resources for the paper [GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction](https://huggingface.co/papers/2509.18090), which presents an explicit voxel-based framework for accurate, detailed, and complete surface reconstruction. |
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* [📚 Paper](https://huggingface.co/papers/2509.18090) |
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* [🌐 Project Page](https://fictionarry.github.io/GeoSVR-project/) |
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* [💻 Code](https://github.com/Fictionarry/GeoSVR) |
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## Reconstruction on Tanks and Temples and DTU Datasets |
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Here we provide the reconstructed meshes of the paper's experiments from GeoSVR. |
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You can browse all the released meshes at: |
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- `meshes_complete/`: The complete meshes of the two datasets. |
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- `DTU_meshes_eval/`: The meshes on DTU datasets, with strict filtering strategy for evaluation. |
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- `TnT_meshes_eval/`: The meshes on TnT datasets, with strict filtering strategy for evaluation. |
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Metrics shall be reproduced with the results with postfix of `_eval`. |
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## Download |
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```python |
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from huggingface_hub import snapshot_download |
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snapshot_download(repo_id="Fictionary/GeoSVR", cache_dir='./GeoSVR/results', local_dir ='./GeoSVR/results') |
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``` |
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or use Git to clone this repository with LFS. |
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## Citation |
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```bibtex |
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@article{li2025geosvr, |
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title={GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction}, |
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author={Li, Jiahe and Zhang, Jiawei and Zhang, Youmin and Bai, Xiao and Zheng, Jin and Yu, Xiaohan and Gu, Lin}, |
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journal={Advances in Neural Information Processing Systems}, |
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year={2025} |
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} |
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``` |
