Create README.md

README.md

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+---
+tags:
+- model_hub_mixin
+- pytorch_model_hub_mixin
+- computer-vision
+- 3d-reconstruction
+- multi-view-stereo
+- depth-estimation
+- camera-pose
+- covisibility
+- mapanything
+license: cc-by-nc-4.0
+language:
+- en
+pipeline_tag: image-to-3d
+---
+
+## Overview
+
+MapAnything is a simple, end-to-end trained transformer model that directly regresses the factored metric 3D geometry of a scene given various types of modalities as inputs. A single feed-forward model supports over 12 different 3D reconstruction tasks including multi-image sfm, multi-view stereo, monocular metric depth estimation, registration, depth completion and more.
+
+This is the CC-BY-NC-4.0 variant of the model released in September 2025, i.e., the V1 version.
+
+## Quick Start
+
+Please refer to our [Github Repo](https://github.com/facebookresearch/map-anything)
+
+## Citation
+
+If you find our repository useful, please consider giving it a star ⭐ and citing our paper in your work:
+
+```bibtex
+@inproceedings{keetha2026mapanything,
+  title={{MapAnything}: Universal Feed-Forward Metric 3D Reconstruction},
+  author={Keetha, Nikhil and M{\"u}ller, Norman and Sch{\"o}nberger, Johannes and Porzi, Lorenzo and Zhang, Yuchen and Fischer, Tobias and Knapitsch, Arno and Zauss, Duncan and Weber, Ethan and Antunes, Nelson and others},
+  booktitle={International Conference on 3D Vision (3DV)},
+  year={2026},
+  organization={IEEE}
+}
+```