Update README.md

README.md

@@ -10,9 +10,14 @@ configs:
   - split: test_unseen
     path: viewer/test_unseen_metadata.csv
 ---
-# GestureHYDRA: Semantic Co-speech Gesture Synthesis via Hybrid Modality Diffusion Transformer and Cascaded-Synchronized Retrieval-Augmented Generation.ICCV 2025
+# Streamer Dataset
 
+Streamer is a co-speech gesture dataset with paired audio and 3D human motion from live streamers, introduced in **GestureHYDRA: Semantic Co-speech Gesture Synthesis via Hybrid Modality Diffusion Transformer and Cascaded-Synchronized Retrieval-Augmented Generation (ICCV 2025)**.
 
+- [Paper (arXiv:2507.22731)](https://arxiv.org/abs/2507.22731)
+- [Paper (ICCV 2025 proceedings)](https://openaccess.thecvf.com/content/ICCV2025/html/Yang_GestureHYDRA_Semantic_Co-speech_Gesture_Synthesis_via_Hybrid_Modality_Diffusion_Transformer_ICCV_2025_paper.html)
+- [Project page](https://mumuwei.github.io/GestureHYDRA/)
+- [Code and usage instructions](https://github.com/hlyyyyy/GestureHydra)
 
 ## Dataset description
 - The Streamer dataset we proposed consists of 281 anchors and 20,969 clips of data.
@@ -21,7 +26,7 @@ configs:
 - The unseen test set contains 998 clips of data, where the anchor ID has never appeared in the training set.
 
 ## Dataset structure 
-The dataset contains three folders: *train*, *test_seen*, and *test_unseen*. Let's *train* train as an example for introduction.
+The dataset contains three folders: *train*, *test_seen*, and *test_unseen*. The *train* split is shown below as an example.
 
 ```plaintext
 -train/
@@ -57,3 +62,23 @@ Data contained in the pkl file:
 - leye_pose: (bs,3)
 - reye_pose: (bs,3)
 - pose_embedding: (bs,32)
+
+## Citation
+
+If you use Streamer in your research, please cite the GestureHYDRA paper:
+
+```bibtex
+@InProceedings{Yang_2025_ICCV,
+  author    = {Yang, Quanwei and Huang, Luying and Wang, Kaisiyuan and Guan, Jiazhi and He, Shengyi and Li, Fengguo and Zhou, Hang and Yu, Lingyun and Li, Yingying and Feng, Haocheng and Xie, Hongtao},
+  title     = {{GestureHYDRA}: Semantic Co-speech Gesture Synthesis via Hybrid Modality Diffusion Transformer and Cascaded-Synchronized Retrieval-Augmented Generation},
+  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
+  month     = {October},
+  year      = {2025},
+  pages     = {12615--12625},
+  url       = {https://openaccess.thecvf.com/content/ICCV2025/html/Yang_GestureHYDRA_Semantic_Co-speech_Gesture_Synthesis_via_Hybrid_Modality_Diffusion_Transformer_ICCV_2025_paper.html}
+}
+```
+
+## License
+
+This dataset is licensed under [Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/), as specified in this repository's metadata.