Update README.md

README.md

@@ -1,3 +1,62 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+## 🚀 Dataset Usage
+To facilitate researchers, we provide the processed streaming 272-dim Motion Representation of [BABEL](https://babel.is.tue.mpg.de/) dataset in this Hugging Face repo.
+
+NOTE: We process the original BABEL dataset to support training of streaming motion generation.
+e.g. If there is a motion sequence A, annotated as (A1, A2, A3, A4) in BABEL dataset, each subsequence has text description: (A1_t, A2_t, A3_t, A4_t).
+
+Then, our BABEL-stream is constructed as:
+
+seq1: (A1, A2)  ---  seq1_text: (A1_t*A2_t#A1_length)
+
+seq2: (A2, A3)  ---  seq2_text: (A2_t*A3_t#A2_length)
+
+seq3: (A3, A4)  ---  seq3_text: (A3_t*A4_t#A3_length)
+
+Here, * and # is separation symbol, A1_length means the number of frames of subsequence A1.
+
+Motions are resampled into 30 FPS.
+
+The dataset is organized as:
+```
+./
+  ├── train_stream
+      ├── seq1.npy
+      ...
+  ├── train_stream_text
+      ├── seq1.txt
+      ...
+  ├── val_stream
+      ├── seq1.npy
+      ...
+  ├── val_stream_text
+      ├── seq1.txt
+      ...
+```
+
+❗️❗️❗️ The processed data is solely for academic purposes. Make sure you read through the [BABEL License](https://babel.is.tue.mpg.de/license.html).
+
+## 📖 Paper & Project Page & Code
+* [Arxiv Paper](https://arxiv.org/abs/2503.15451)
+* [Project Page](https://zju3dv.github.io/MotionStreamer/)
+* [Code](https://github.com/zju3dv/MotionStreamer)
+
+## 🏃 Processing script
+For more details of how to obtain the 272-dim motion representation, as well as other useful tools (e.g., Visualization and Conversion to BVH format), please refer to our [GitHub repo](https://github.com/Li-xingXiao/272-dim-Motion-Representation).
+
+## 🌹 Acknowledgement
+This repository builds upon the following awesome datasets and projects:
+- [BABEL](https://babel.is.tue.mpg.de/)
+
+## 🤝🏼 Citation
+If our project is helpful for your research, please consider citing :
+``` 
+@article{xiao2025motionstreamer,
+      title={MotionStreamer: Streaming Motion Generation via Diffusion-based Autoregressive Model in Causal Latent Space},
+      author={Xiao, Lixing and Lu, Shunlin and Pi, Huaijin and Fan, Ke and Pan, Liang and Zhou, Yueer and Feng, Ziyong and Zhou, Xiaowei and Peng, Sida and Wang, Jingbo},
+      journal={arXiv preprint arXiv:2503.15451},
+      year={2025}
+    }
+```