| | --- |
| | pipeline_tag: robotics |
| | library_name: diffusers |
| | license: mit |
| | --- |
| | |
| | # Real-Time Iteration Scheme for Diffusion Policy (RTI-DP) |
| |
|
| | This repository contains the official model weights and code for the paper: **"Real-Time Iteration Scheme for Diffusion Policy"**. |
| |
|
| | - 📚 [Paper](https://huggingface.co/papers/2508.05396) |
| | - 🌐 [Project Page](https://rti-dp.github.io/) |
| | - 💻 [Code](https://github.com/RTI-DP/rti-dp) |
| |
|
| | RTI-DP enables fast inference in diffusion-based robotic policies by initializing each denoising step with the previous prediction — no retraining, no distillation. |
| |
|
| | <div align="center"> |
| | <img src="https://rti-dp.github.io/static/images/rti.png" alt="RTI-DP Teaser" width="600"/> |
| | </div> |
| |
|
| | ## Usage |
| |
|
| | This model is designed to be used with its official codebase. For detailed installation instructions, environment setup, and further information, please refer to the [official GitHub repository](https://github.com/RTI-DP/rti-dp), which is based on [Diffusion Policy](https://github.com/real-stanford/diffusion_policy). |
| |
|
| | ### Evaluation |
| |
|
| | To evaluate RTI-DP policies with DDPM, you can use the provided script from the repository: |
| |
|
| | ```shell |
| | python ../eval_rti.py --config-name=eval_diffusion_rti_lowdim_workspace.yaml |
| | ``` |
| |
|
| | For RTI-DP-scale checkpoints, refer to the [duandaxia/rti-dp-scale](https://huggingface.co/duandaxia/rti-dp-scale) on Hugging Face. |
| |
|
| | ## Citation |
| |
|
| | If you find our work useful, please consider citing our paper: |
| |
|
| | ```bibtex |
| | @misc{duan2025realtimeiterationschemediffusion, |
| | title={Real-Time Iteration Scheme for Diffusion Policy}, |
| | author={Yufei Duan and Hang Yin and Danica Kragic}, |
| | year={2025}, |
| | eprint={2508.05396}, |
| | archivePrefix={arXiv}, |
| | primaryClass={cs.RO}, |
| | url={https://arxiv.org/abs/2508.05396}, |
| | } |
| | ``` |
| |
|
| | ## Acknowledgements |
| |
|
| | We thank the authors of [Diffusion Policy](https://github.com/real-stanford/diffusion_policy), [Consistency Policy](https://github.com/Aaditya-Prasad/Consistency-Policy/) and [Streaming Diffusion Policy](https://github.com/Streaming-Diffusion-Policy/streaming_diffusion_policy/) for sharing their codebase. |
