Update README.md

README.md

@@ -1,3 +1,67 @@
----
-license: mit
----
+---
+license: mit
+language:
+- en
+tags:
+- material
+- pbr
+- svbrdf
+- texture
+- editing
+---
+
+
+# MatFuse: Controllable Material Generation with Diffusion Models
+
+## 🧩 Model Overview
+
+MatFuse leverages diffusion models to simplify the creation of Spatially-Varying Bidirectional Reflectance Distribution Function (SVBRDF) maps. 
+It allows for fine-grained control over material synthesis through multiple conditioning sources like color palettes, sketches, text, and images. 
+Additionally, it supports post-generation editing of materials.
+
+For more details, visit the [project page](https://gvecchio.com/matfuse/) or read the full paper on [arXiv](https://arxiv.org/abs/2308.11408).
+
+## 🧑‍💻 Usage
+
+### 💿 Installation
+
+1. Clone the repository:
+    ```bash
+    git clone https://github.com/giuvecchio/matfuse-sd.git
+    cd matfuse-sd
+    ```
+
+2. Set up the environment:
+    ```bash
+    # create environment (can use venv instead of conda)
+    conda create -n matfuse python==3.10.13
+    conda activate matfuse
+    # install required packages
+    pip install -r requirements.txt
+    ```
+    
+3. Download the checkpoint.
+
+### 🧪 Inference
+
+To run inference on a trained model:
+```bash
+python src/gradio_app.py --ckpt <path/to/checkpoint.ckpt> --config src/configs/diffusion/<config.yaml>
+```
+
+## 📜 Citation
+
+```bibtex
+@inproceedings{vecchio2024matfuse,
+  author    = {Vecchio, Giuseppe and Sortino, Renato and Palazzo, Simone and Spampinato, Concetto},
+  title     = {MatFuse: Controllable Material Generation with Diffusion Models},
+  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  month     = {June},
+  year      = {2024},
+  pages     = {4429-4438}
+}
+```
+
+## License
+
+This project is licensed under the MIT License.