Update README.md

README.md

@@ -1,3 +1,47 @@
 ---
-license: apache-2.0
+license: cc-by-nc-4.0
+base_model: Depth-Anything/Depth-Anything-3
+tags:
+  - 3d-reconstruction
+  - visual-slam
+  - pose-estimation
+  - depth-estimation
+  - computer-vision
 ---
+
+# R³: 3D Reconstruction via Relative Regression
+
+## Model Description
+
+R³ is a feed-forward model for long-video 3D reconstruction via confidence-weighted relative pose regression.
+
+Built on top of the Depth Anything 3 (DA3) backbone, R³ predicts pairwise relative camera poses and dense geometry from arbitrarily long video streams. Instead of directly regressing all cameras in a global coordinate frame, R³ estimates confidence-weighted relative transformations between image pairs and assembles a globally consistent trajectory downstream.
+
+With approximately 372M parameters, R³ achieves competitive or state-of-the-art performance on camera pose estimation and dense reconstruction benchmarks while remaining significantly smaller than recent billion-parameter alternatives.
+
+## License
+
+This model is a derivative work based on the Depth Anything 3 (DA3) model.
+
+The original DA3 model is released under the CC BY-NC 4.0 license. Accordingly, this model is also distributed under the CC BY-NC 4.0 license and may only be used in accordance with the terms of that license.
+
+Commercial use is not permitted without obtaining appropriate permissions from the original rights holders.
+
+## Model Details
+
+- **Model Type:** 3D Reconstruction / Visual Localization
+- **Backbone:** Depth Anything 3 (DA3)
+- **Parameters:** ~372M
+- **Task:** Relative Pose Regression and Dense 3D Reconstruction
+
+## Citation
+
+If you use this model in your research, please cite the R³ paper.
+
+```bibtex
+@misc{xu2026r3,
+      title={$R^3$: 3D Reconstruction via Relative Regression},
+      author={Congrong Xu and Huachen Gao and Xingyu Chen and Yuliang Xiu and Jun Gao and Anpei Chen},
+      year={2026},
+}
+```