Add model card for GaMO

This PR adds a comprehensive model card for GaMO, including relevant metadata, links to the paper, project page, and official GitHub repository, as well as the BibTeX citation.

README.md

@@ -1,3 +1,25 @@
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-license: apache-2.0
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+---
+license: apache-2.0
+pipeline_tag: image-to-image
+---
+
+# GaMO: Geometry-aware Multi-view Diffusion Outpainting for Sparse-View 3D Reconstruction
+
+[**Project Page**](https://yichuanh.github.io/GaMO/) | [**ArXiv**](https://huggingface.co/papers/2512.25073) | [**GitHub**](https://github.com/yichuanH/GaMO_official)
+
+GaMO (Geometry-aware Multi-view Outpainter) is a framework that reformulates sparse-view reconstruction through multi-view outpainting. Instead of generating new viewpoints, GaMO expands the field of view from existing camera poses, which inherently preserves geometric consistency while providing broader scene coverage.
+
+Our approach employs multi-view conditioning and geometry-aware denoising strategies in a zero-shot manner without training. Extensive experiments on Replica and ScanNet++ demonstrate state-of-the-art reconstruction quality across 3, 6, and 9 input views, outperforming prior methods in PSNR and LPIPS, while achieving a 25× speedup over SOTA diffusion-based methods.
+
+## Citation
+
+If you find this work useful, please consider citing:
+
+```bibtex
+@article{huang2025gamo,
+  title={GaMO: Geometry-aware Multi-view Diffusion Outpainting for Sparse-View 3D Reconstruction},
+  author={Huang, Yi-Chuan and Chien, Hao-Jen and Lin, Chin-Yang and Chen, Ying-Huan and Liu, Yu-Lun},
+  journal={arXiv preprint arXiv:2512.25073},
+  year={2025}
+}
+```