|
|
--- |
|
|
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} |
|
|
} |
|
|
``` |
