Update README.md

README.md

@@ -2,8 +2,45 @@
 tags:
 - pytorch_model_hub_mixin
 - model_hub_mixin
+- image-to-3d
+library_name: dust3r
 ---
 
-This model has been pushed to the Hub using ****:
-- Repo: [More Information Needed]
-- Docs: [More Information Needed]
+## DUSt3R: Geometric 3D Vision Made Easy
+
+```bibtex
+@inproceedings{dust3r_cvpr24,
+      title={DUSt3R: Geometric 3D Vision Made Easy}, 
+      author={Shuzhe Wang and Vincent Leroy and Yohann Cabon and Boris Chidlovskii and Jerome Revaud},
+      booktitle = {CVPR},
+      year = {2024}
+}
+```
+
+# License
+The code is distributed under the CC BY-NC-SA 4.0 License. See [LICENSE](https://github.com/naver/dust3r/blob/main/LICENSE) for more information.
+For the checkpoints, make sure to agree to the license of all the public training datasets and base checkpoints we used, in addition to CC-BY-NC-SA 4.0. See [section: Our Hyperparameters](https://github.com/naver/dust3r?tab=readme-ov-file#our-hyperparameters) for details.
+
+# Model info
+
+Gihub page: https://github.com/naver/dust3r/
+Project page: https://dust3r.europe.naverlabs.com/
+
+| Modelname   | Training resolutions | Head | Encoder | Decoder |
+|-------------|----------------------|------|---------|---------|
+| DUSt3R_ViTLarge_BaseDecoder_224_linear | 224x224 | Linear | ViT-L | ViT-B |
+
+# How to use
+
+First, [install dust3r](https://github.com/naver/dust3r?tab=readme-ov-file#installation). Make sure to install the huggingface-hub[torch]>=0.22 optional dependency.
+To load the model:
+
+```python
+from dust3r.model import AsymmetricCroCo3DStereo
+import torch
+
+model = AsymmetricCroCo3DStereo.from_pretrained("naver/DUSt3R_ViTLarge_BaseDecoder_224_linear")
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+```