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Official Code for Epona: Autoregressive Diffusion World Model for Autonomous Driving (ICCV 2025)
| Date | Stars |
|---|---|
| 2026-07-24 | 374 |
| 2026-07-25 | 374 |
| 2026-07-28 | 376 |
| 2026-07-30 | 376 |
| 2026-08-06 | 376 |
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<p align="center">
<h1 align="center"><i>Epona</i>: Autoregressive Diffusion World Model for Autonomous Driving</h1>
<h3 align="center">ICCV 2025</h3>
<p align="center">
<span class="author-block">
<a href="https://kevin-thu.github.io/homepage/" target="_blank">Kaiwen Zhang</a><sup>*</sup>,
</span>
<span class="author-block">
<a href="https://github.com/Tzy010822/" target="_blank">Zhenyu Tang</a><sup>*</sup>,
</span>
<span class="author-block">
<a href="https://huxiaotaostasy.github.io/" target="_blank">Xiaotao Hu</a>,
</span>
<span class="author-block">
<a href="https://xingangpan.github.io/" target="_blank">Xingang Pan</a>,
</span><br>
<span class="author-block">
<a href="https://xy-guo.github.io/" target="_blank">Xiaoyang Guo</a>,
</span>
<span class="author-block">
<a href="https://liuyuan-pal.github.io/" target="_blank">Yuan Liu</a>,
</span>
<span class="author-block">
<a href="https://scholar.google.com/citations?user=7eJBk1UAAAAJ&hl=zh-CN" target="_blank">Jingwei Huang</a>,
</span>
<span class="author-block">
<a href="https://yuanli2333.github.io/" target="_blank">Yuan Li</a>,
</span>
<span class="author-block">
<a href="https://scholar.google.com/citations?user=pCY-bikAAAAJ&hl=en&oi=ao" target="_blank">Qian Zhang</a>,
</span><br>
<span class="author-block">
<a href="https://www.xxlong.site/" target="_blank">Xiaoxiao Long</a><sup>✝</sup>,
</span>
<span class="author-block">
<a href="https://cite.nju.edu.cn/People/Faculty/20190621/i5054.html" target="_blank">Xun Cao</a>,
</span>
<span class="author-block">
<a href="https://yvanyin.xyz/" target="_blank">Wei Yin</a><sup>§</sup>
</p>
<p align="center">
<sep>*</sep>Equal Contribution
<sep>✝</sep>Project Adviser
<sep>§</sep>Project Lead, Corresponding Author
</p>
<p align="center">
<a href="https://arxiv.org/pdf/2506.24113"><img alt='arXiv' src="https://img.shields.io/badge/arXiv-2506.24113-b31b1b.svg"></a>
<a href="https://kevin-thu.github.io/Epona/"><img alt='page' src="https://img.shields.io/badge/Project-Website-orange"></a>
<a href="https://huggingface.co/Kevin-thu/Epona"><img alt="Huggingface" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Epona-orange"></a>
<!-- <a href="https://twitter.com/sze68zkw"><img alt='Twitter' src="https://img.shields.io/twitter/follow/sze68zkw?label=%40KaiwenZhang"></a> -->
</p>
<div align="center">
<img src="./assets/teaser.png", width="800">
<p align="left"><b>Versatile capabilities of <i>Epona</i></b>: Given historical driving context, our Epona can generate consistent <b>minutes-long driving videos</b> at high resolution (A). It can be <b>controlled by diverse trajectories</b> (B), and understand real-world traffic knowledge (C). In addition, our world model can <b>predict future trajectories</b> and serve as an end-to-end real-time motion planner (D).
</p>
</div>
</p>
## 🚀 Getting Started
### Installation
```bash
conda create -n epona python=3.10
conda activate epona
pip install -r requirements.txt
```
To run the code with CUDA properly, you can comment out `torch` and `torchvision` in `requirement.txt`, and install the appropriate version of `torch>=2.1.0+cu121` and `torchvision>=0.16.0+cu121` according to the instructions on [PyTorch](https://pytorch.org/get-started/locally/).
### Data Preparation
Please refer to [data preparation](./data_preparation/README.md) for more details to prepare and preprocess data.
After preprocessing, please change the `datExcerpt of 9,267 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ea5e081d26126c7d, topic:autonomous-driving, desc:autonomous driving, readme:autonomous driving
matched fp:ea5e081d26126c7d, topic:diffusion-models
matched fp:ea5e081d26126c7d, topic:video-generation