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SAMatcher

SAMatcher is a feature matching framework that formulates correspondence estimation through co-visibility modeling. Built upon the Segment Anything Model (SAM), it introduces a symmetric cross-view interaction...

TipoOtherModelo basesyscv-community/sam-hq-vit-largeVersiónRevision 03ccaf1Ccalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
915 MB
Modelo base
syscv-community/sam-hq-vit-large
Versión
vRevision 03ccaf1
Actualizado
1 nov 2026
Descargas
0
Fuente
Hugging Face

Descripción de la fuente

SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching

SAMatcher is a feature matching framework that formulates correspondence estimation through co-visibility modeling. Built upon the Segment Anything Model (SAM), it introduces a symmetric cross-view interaction mechanism that enables bidirectional feature exchange and cross-view semantic alignment to improve correspondence under large viewpoint, illumination, and scale variations.

Quick Start

Installation

The project uses uv for dependency management. Recommended Python version is 3.12.

# Clone the repository
git clone https://github.com/TwSphinx54/SAMatcher.git
cd SAMatcher

# Install dependencies using uv
uv sync --frozen

Download Weights

You can download the model weights using the Hugging Face CLI:

huggingface-cli download SSSSphinx/SAMatcher --local-dir ./weights/SAMatcher

Then follow the official training/evaluation scripts in the GitHub repository.

Evaluation

To evaluate on MegaDepth, use the provided script:

bash scripts/evaluate_megadepth.sh

Citation

If you find SAMatcher useful in your research, please consider citing:

@article{pan2024samatcher,
  title={SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching},
  author={Pan, Xu and Ma, Qiyuan and Zhang, Jintao and Chen, He and Zheng, Xianwei},
  journal={arXiv preprint arXiv:2606.03406},
  year={2024}
}

Fuentes

1 fuente
Hugging FacePrincipalVersión 03ccaf1a396a224da2591ccb8169e0121f29ccf4
huggingface.co/SSSSphinx/SAMatcher/tree/03ccaf1a396a224da2591ccb8169e0121f29ccf4

Verificado 1 nov

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Artefactos del modelo

1 artefacto

weights/samatcher_best.ckpt

ckpt · 915 MB · SHA-256 454fd8b1dde2…28d7 · Hugging Face

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Extractos de fuentes

2 extractos

--- base_model: - syscv-community/sam-hq-vit-large language: - en license: apache-2.0 pipeline_tag: image-segmentation tags: - feature-matching - computer-vision - co-visibility --- # SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching SAMatcher is a feature matching framework that formulates correspondence estimation through co-visibility modeling. Built upon the Segment Anything Model (SAM), it introduces a symmetric cross-view interaction mechanism that enables bidirectional feature exchange and cross-view semantic alignment to improve correspondence under large viewpoint, illumination, and scale variations. - **Paper:** [SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching](https://huggingface.co/papers/2606.03406) - **Authors:** Xu Pan, Qiyuan Ma, Jintao Zhang, He Chen, Xianwei Zheng - **GitHub:** [https://github.com/TwSphinx54/SAMatcher](https://github.com/TwSphinx54/SAMatcher) - **Project Page:** [https://xupan.top/Projects/samatcher](https://xupan.top/Projects/samatcher) ## Quick Start ### Installation The project uses `uv` for dependency management. Recommended Python version is 3.12. ```bash # Clone the repository git clone https://github.com/TwSphinx54/SAMatcher.git cd SAMatcher # Install dependencies using uv uv sync --frozen ``` ### Download Weights You can download the model weights using the Hugging Face CLI: ```bash huggingface-cli download SSSSphinx/SAMatcher --local-dir ./weights/SAMatcher ``` Then follow the official training/evaluation scripts in the GitHub repository. ## Evaluation To evaluate on MegaDepth, use the provided script: ```bash bash scripts/evaluate_megadepth.sh ``` ## Citation If you find SAMatcher useful in your research, please consider citing: ```bibtex @article{pan2024samatcher, title={SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching}, author={Pan, Xu and Ma, Qiyuan and Zhang, Jintao and Chen, He and Zheng, Xianwei}, journal={arXiv preprint arXiv:2606.03406}, year={2024} } ```

Source context: 0 downloads · 0 likes · Pipeline image-segmentation · Repo SSSSphinx/SAMatcher