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# MapAnything Dataset
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## Dataset Description
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This dataset contains pre-computed metadata and covisibility matrices for supporting the [MapAnything codebase](https://github.com/facebookresearch/map-anything). This metadata enables easy reproducible training
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Please see our [Data Processing README](https://github.com/facebookresearch/map-anything/data_processing/README.md) for more details.
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If you use this dataset in your research, please cite our paper:
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```bibtex
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@inproceedings{
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title={{MapAnything}: Universal Feed-Forward Metric {3D} Reconstruction},
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author={Nikhil Keetha and Norman
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booktitle={
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year={
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```
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## License
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## Links
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# MapAnything Training Metadata Dataset
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## Dataset Description
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This dataset contains pre-computed metadata and covisibility matrices for supporting the [MapAnything codebase](https://github.com/facebookresearch/map-anything). This metadata enables easy reproducible training for feed-forward 3D reconstruction tasks.
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Please see our [Data Processing README](https://github.com/facebookresearch/map-anything/data_processing/README.md) for more details.
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If you use this dataset in your research, please cite our paper:
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```bibtex
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@inproceedings{keetha2026mapanything,
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title={{MapAnything}: Universal Feed-Forward Metric {3D} Reconstruction},
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author={Nikhil Keetha and Norman M\"{u}ller and Johannes Sch\"{o}nberger and Lorenzo Porzi and Yuchen Zhang and Tobias Fischer and Arno Knapitsch and Duncan Zauss and Ethan Weber and Nelson Antunes and Jonathon Luiten and Manuel Lopez-Antequera and Samuel Rota Bul\`{o} and Christian Richardt and Deva Ramanan and Sebastian Scherer and Peter Kontschieder},
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booktitle={International Conference on 3D Vision (3DV)},
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year={2026},
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organization={IEEE}
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}
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```
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## License
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The metadata is released under the [Apache 2.0 License](https://github.com/facebookresearch/map-anything/LICENSE).
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## Links
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