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README.md

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+<div align="center">
+  <img src="assets/teaser.png">
+
+<a href="https://hyokong.github.io/worldwarp-page/"><h1>🌏 WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion 🌀</h1></a>
+</h2>
+</div>
+
+<h5 align="center">
+
+[![Home Page](https://img.shields.io/badge/Project-Website-33728E.svg)](https://hyokong.github.io/worldwarp-page/) 
+[![arXiv](https://img.shields.io/badge/Arxiv-2509.26645-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2509.26645) 
+[![HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Demo-blue)](https://huggingface.co/imsuperkong/worldwarp) [![Watch on YouTube](https://img.shields.io/badge/YouTube-Demo_Video-red?style=flat&logo=youtube)](https://www.youtube.com/watch?v=rfMHxb--cKs)
+
+
+[Hanyang Kong](https://hyokong.github.io/),
+[Xingyi Yang](https://adamdad.github.io/),
+Xiaoxu Zheng,
+[Xinchao Wang](https://sites.google.com/site/sitexinchaowang/)
+</h5>
+
+**TL;DR**: 🔭 Single-image long-range view generation via an <u>asynchronous chunk-wise autoregressive diffusion framework</u> that utilizes <u>explicit camera conditioning</u> and <u>online 3D cache</u> for geometric consistency.
+
+
+## 🎬 Demo Video
+
+▶️ **Click the GIF to watch the full video with sound.**
+
+<p align="center">
+  <a href="https://www.youtube.com/watch?v=rfMHxb--cKs">
+    <img src="assets/web_teaser.gif" alt="WorldWarp Demo" width="100%">
+  </a>
+</p>
+
+## 🛠️ Installation
+
+> ⚠️ **Hardware Note:** The current implementation requires high GPU memory (~40GB VRAM). We are currently optimizing the code to reduce this footprint.
+
+### 🧬 Cloning the Repository
+The repository contains submodules, thus please check it out with
+```bash
+git clone https://github.com/HyoKong/WorldWarp.git --recursive
+cd WorldWarp
+```
+
+### 🐍 Create environment
+
+Create a conda environment and install dependencies:
+```
+conda create -n worldwarp python=3.12 -y
+conda activate worldwarp
+```
+
+### 🔥 Install PyTorch
+Install PyTorch with CUDA 12.6 support (or visit [PyTorch Previous Versions](https://pytorch.org/get-started/previous-versions/) for other CUDA configurations):
+```bash
+pip install torch==2.7.1 torchvision==0.22.1 torchaudio==2.7.1 --index-url https://download.pytorch.org/whl/cu126
+```
+
+### 📦 Install Dependencies & Compile Extensions
+These packages require compilation against the specific PyTorch version installed above.
+
+```bash
+# Core compiled dependencies
+pip install flash-attn --no-build-isolation
+pip install "git+https://github.com/facebookresearch/pytorch3d.git" --no-build-isolation
+
+# Local modules
+pip install src/fused-ssim/ --no-build-isolation
+pip install src/simple-knn/ --no-build-isolation
+
+# Remaining python dependencies
+pip install -r requirements.txt
+```
+
+
+
+### 🏗️ Build Other Extensions
+```bash
+cd src/ttt3r/croco/models/curope/
+python setup.py build_ext --inplace
+cd -  # Returns to the project root
+```
+
+
+## ☁️ Download checkpoints
+
+```
+mkdir ckpt
+hf download Wan-AI/Wan2.1-T2V-1.3B-Diffusers --local-dir ckpt/Wan-AI/Wan2.1-T2V-1.3B-Diffusers
+hf download Qwen/Qwen2.5-VL-7B-Instruct --local-dir ckpt/Qwen/Qwen2.5-VL-7B-Instruct
+hf download imsuperkong/worldwarp --local-dir ckpt/
+
+cd src/ttt3r/
+gdown --fuzzy https://drive.google.com/file/d/1Asz-ZB3FfpzZYwunhQvNPZEUA8XUNAYD/view?usp=drive_link
+cd ../..
+```
+
+## 🎨 GUI Demo
+
+```bash
+python gradio_demo.py
+```
+
+The web interface will open at `http://localhost:7890`. 
+
+---
+
+### 🚀 Quick start:
+
+**1️⃣ Choose Starting Image**
+
+- **📚 Examples Tab**: Click a pre-made example image (prompt auto-fills)
+- **🎨 Generate Tab**: Click "Generate First Frame" from your prompt
+- **📤 Upload Tab**: Upload your own image
+
+**2️⃣ Select Camera Movement** (Recommended: 📹 From Video)
+
+- **From Video** (Easiest and most reliable)
+  - Click **"📹 From Video"** mode
+  - Select an example video from the gallery OR upload your own
+  - Click **"🎯 Load Poses"** to extract camera trajectory
+  - Poses are automatically cached for reuse
+
+- **Preset Movements**
+  - Select **"🎯 Preset"** mode
+  - Choose movements: `DOLLY_IN`, `PAN_LEFT`, `PAN_RIGHT`, etc.
+  - Can combine: e.g., `DOLLY_IN + PAN_RIGHT`
+
+- **Custom** (Advanced)
+  - Select **"🔧 Custom"** mode
+  - Manually control rotation and translation parameters
+
+**3️⃣ Configure & Generate**
+
+**Essential Parameters:**
+
+- 💪 **Strength (0.5 - 0.8)**
+  - **Higher (0.7-0.8)**: More generated details, richer content
+    - ⚠️ May introduce content changes due to higher creative freedom
+  - **Lower (0.5-0.6)**: More accurate camera control, closer to input
+    - ⚠️ May produce blurry results due to limited diffusion model freedom
+  - **Trade-off**: Higher strength = more details but less control; Lower strength = better control but potentially blurry
+
+- ⚡ **Speed Multiplier**
+  - **Purpose**: Adjust camera movement velocity to match your scene scale
+  - **Why needed**: Reference video's camera movement scale may not match your scene (e.g., drone video moving 10 meters may be too fast for a small room)
+  - **< 1.0**: Slower camera movement (e.g., 0.5 = half speed)
+  - **= 1.0**: Original speed from reference
+  - **> 1.0**: Faster camera movement (e.g., 2.0 = double speed)
+  - **Tip**: Start with 1.0, then adjust based on whether motion feels too fast or too slow
+
+---
+
+#### 🌟 Best Practices
+
+- 👁️ **Generate one chunk at a time**
+  - Lets you preview each chunk's quality before continuing
+  - Easier to identify issues early
+
+- ↩️ **Use Rollback for iteration**
+  - If a chunk is unsatisfactory, enter its number in **"Rollback to #"**
+  - Click **"✂️ Rollback"** to remove it
+  - Adjust parameters and regenerate
+
+- 🏎️ **Adjust Speed Multiplier per scene**
+  - If camera moves too fast → decrease value (e.g., 0.5-0.7)
+  - If camera moves too slow → increase value (e.g., 1.5-2.0)
+
+
+
+
+
+
+## 🙌 Acknowledgements
+Our code is based on the following awesome repositories:
+
+- [DFoT](https://github.com/kwsong0113/diffusion-forcing-transformer)
+- [TTT3R](https://github.com/Inception3D/TTT3R)
+
+We thank the authors for releasing their code!
+
+## 📖 Citation
+
+If you find our work useful, please cite:
+
+```bibtex
+@misc{kong2025worldwarp,
+  title={WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion}, 
+  author={Hanyang Kong and Xingyi Yang and Xiaoxu Zheng and Xinchao Wang},
+  year={2025},
+  eprint={2512.xxxxx},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV}
+}
+```

assets/web_teaser.mp4

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