AnchorSplat 20x

--- license: mit library_name: pytorch tags: - computer-vision - 3d-gaussian-splatting - gaussian-splatting - super-resolution - eccv-2026 - pytorch pipeline_tag: image-to-3d --- # AnchorSplat 20x Checkpoint This repository hosts the released 20x checkpoint for **AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splatting (ECCV 2026)**. - Paper: https://arxiv.org/abs/2607.01290 - Code: https://github.com/zhude233/AnchorSplat - Checkpoint: `anchorsplat_20x.pth` - SHA256: `ad05f8b965c002c1f62cea53e4ce10ed4804bbc433375afa5f411f236d1b79a3` ## Usage Download the checkpoint and place it at: ```text checkpoints/anchorsplat_20x.pth ``` or pass it explicitly: ```bash WEIGHTS=/path/to/anchorsplat_20x.pth \ bash scripts/inference_external.sh examples/lgm_sample.ply outputs/lgm_sample_refined.ply lgm ``` ## Notes AnchorSplat is designed for fast, generalizable, plug-and-play enhancement of low-quality 3D Gaussian Splatting assets. For external PLY inputs, please follow the input format and normalization instructions in the GitHub README. ## Citation ```bibtex @article{zhu2026anchorsplat, title={AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splatting}, author={Zhu, Dexu and Shao, Jiangnan and Wang, Xiaofeng and Duan, Junxian and Cao, Jie and Zhu, Zheng and Huang, Huaibo}, journal={arXiv preprint arXiv:2607.01290}, year={2026}, eprint={2607.01290}, archivePrefix={arXiv}, primaryClass={cs.CV}, doi={10.48550/arXiv.2607.01290}, url={https://arxiv.org/abs/2607.01290} } ```

Source context: 0 downloads · 0 likes · Pipeline image-to-3d · Library pytorch · Repo de233/AnchorSplat-20x