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README.md

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----
-license: cc-by-nc-4.0
----
+# Anchor Forcing: Anchor Memory and Tri-Region RoPE for Interactive Streaming Video Diffusion
+
+<a href="https://arxiv.org/abs/2603.13405"><img src='https://img.shields.io/badge/arXiv-2603.13405-red?style=flat&logo=arXiv&logoColor=red' alt='arxiv'></a>&nbsp;
+<a href="https://vivocameraresearch.github.io/anchorforcing/"><img src='https://img.shields.io/badge/Project-Page-Green' alt='page'></a>&nbsp;
+<a href="http://www.apache.org/licenses/LICENSE-2.0"><img src='https://img.shields.io/badge/License-CC BY--NC--SA--4.0-lightgreen?style=flat&logo=Lisence' alt='License'></a><br>
+
+![overview](assets/motivation.jpg)
+<p>
+      📖<strong>TL;DR</strong>: <strong>Anchor Forcing</strong>  enables prompt switches to introduce new subjects and actions while preserving context, motion quality, and temporal coherence; prior methods often degrade over time and miss newly specified interactions.
+</p>
+
+## 📢 News
+- **[2026-03-18]** 🎉 We have officially released the code for public use!  
+
+
+## ✅ ToDo List for Any-to-Bokeh Release
+
+- [x] Release the code
+- [x] Release the inference pipeline
+- [x] Release the training files
+- [x] Release the model weights
+
+## :wrench: Installation
+We tested this repo on the following setup:
+* Nvidia GPU with at least 40 GB memory (A100 tested).
+* Linux operating system.
+* 64 GB RAM.
+
+Other hardware setup could also work but hasn't been tested.
+
+**Environment**
+
+Create a conda environment and install dependencies:
+```
+git clone https://github.com/vivoCameraResearch/Anchor-Forcing.git
+cd Anchor-Forcing
+conda create -n af python=3.10 -y
+conda activate af
+pip install torch==2.6.0 torchvision==0.21.0 --index-url https://download.pytorch.org/whl/cu124
+pip install -r requirements.txt
+pip install flash-attn --no-build-isolation
+
+# Manual installation flash-attention. Recommended version: 2.7.4.post1
+https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu12torch2.6cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
+```
+
+## ⏬ Demo Inference 
+
+**Download Wan2.1-T2V-1.3B**
+```
+huggingface-cli download Wan-AI/Wan2.1-T2V-1.3B --local-dir wan_models/Wan2.1-T2V-1.3B
+```
+
+**Download checkpoints**
+
+```
+huggingface-cli download young98/AnchorForcing --local-dir ckpt
+```
+
+**Single Prompt Video Generation**
+```
+bash inference/inference.sh
+```
+**Interactive Long Video Generation**
+```
+bash inference/interactive_inference.py
+```
+
+
+## Training
+**Download checkpoints**
+
+Please follow [Self-Forcing](https://github.com/guandeh17/Self-Forcing) to download text prompts and ODE initialized checkpoint.
+
+Download Wan2.1-T2V-14B as the teacher model.
+
+```
+huggingface-cli download Wan-AI/Wan2.1-T2V-14B --local-dir wan_models/Wan2.1-T2V-14B
+```
+
+**Step1: Self-Forcing Initialization for Short Window and Frame Sink**
+
+Please follow [LongLive](https://nvlabs.github.io/LongLive/docs/#training:~:text=Step1%3A%20Self%2DForcing%20Initialization%20for%20Short%20Window%20and%20Frame%20Sink) 
+
+**Step2: Streaming Long Tuning**
+```
+bash train.sh
+```
+
+**Hints**
+
+This repository only provides the training code for step 2. We default to following the training method of LongLive's step 1. Therefore, you can directly train step 2 using LongLive's checkpoints.
+
+## 📜 Acknowledgement
+This codebase builds on [LongLive](https://github.com/NVlabs/LongLive). Thanks for open-sourcing! Besides, we acknowledge following great open-sourcing projects:
+- [MemFlow](https://github.com/KlingAIResearch/MemFlow): We followed its interactive video benchmark.
+- [Self-Forcing](https://github.com/guandeh17/Self-Forcing): We followed its vbench prompt and checkpoints.
+
+
+## 🌏 Citation
+
+```bibtex
+@article{yang2026anchor,
+  title={Anchor Forcing: Anchor Memory and Tri-Region RoPE for Interactive Streaming Video Diffusion},
+  author={Yang, Yang and Zhang, Tianyi and Huang, Wei and Chen, Jinwei and Wu, Boxi and He, Xiaofei and Cai, Deng and Li, Bo and Jiang, Peng-Tao},
+  journal={arXiv preprint arXiv:2603.13405},
+  year={2026}
+}
+```
+
+## 📧 Contact
+
+If you have any questions and improvement suggestions, please email Yang Yang (yangyang98@zju.edu.cn), or open an issue.

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