Update model card with metadata, links, and description

README.md

@@ -1 +1,46 @@
-###Coming soon
+---
+pipeline_tag: other
+library_name: diffusers
+---
+
+# SounDiT: Geo-Contextual Soundscape-to-Landscape Generation
+
+SounDiT is a diffusion transformer (DiT)-based model designed for the **Geo-contextual Soundscape-to-Landscape (GeoS2L)** generation task. It synthesizes geographically realistic landscape images from environmental soundscapes by incorporating geo-contextual scene conditioning.
+
+- **Paper:** [SounDiT: Geo-Contextual Soundscape-to-Landscape Generation](https://huggingface.co/papers/2505.12734)
+- **Project Page:** [https://gisense.github.io/SounDiT-Page/](https://gisense.github.io/SounDiT-Page/)
+- **Repository:** [https://github.com/GISense/SounDiT](https://github.com/GISense/SounDiT)
+
+## Overview
+Recent audio-to-image models often struggle to reconstruct real-world landscapes from environmental soundscapes. SounDiT addresses this gap using a DiT architecture that leverages diverse environmental soundscapes and scene conditioning to ensure geographical coherence. To evaluate this task, the authors introduced the Place Similarity Score (PSS) framework, which captures multi-level generation consistency across element, scene, and human perception.
+
+## Code Usage
+
+### Environment Setup
+
+```bash
+conda env create -f environment.yml
+conda activate SounDiT
+```
+
+### Inference
+
+```bash
+bash ./scripts/inference.sh
+```
+
+## Citation
+
+If you use SounDiT in your research, please cite the following paper:
+
+```bibtex
+@misc{wang2025sounditgeocontextualsoundscapetolandscapegeneration,
+  title={SounDiT: Geo-Contextual Soundscape-to-Landscape Generation},
+  author={Junbo Wang and Haofeng Tan and Bowen Liao and Albert Jiang and Teng Fei and Qixing Huang and Zhengzhong Tu and Shan Ye and Yuhao Kang},
+  year={2025},
+  eprint={2505.12734},
+  archivePrefix={arXiv},
+  primaryClass={cs.SD},
+  url={https://arxiv.org/abs/2505.12734}
+}
+```