File size: 5,049 Bytes
b81e177 a3611ea b81e177 d1c6cbe b81e177 d1c6cbe e94eb4c b81e177 9cb1195 e83a8af 92ddba9 fc9a087 9cb1195 b81e177 f4beffa b81e177 25a2e87 b81e177 25a2e87 b81e177 25a2e87 b81e177 be8d073 b81e177 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
---
license: mit
language:
- en
pipeline_tag: image-to-video
library_name: diffusers
base_model:
- Skywork/SkyReels-V2-I2V-1.3B-540P
---
# Matrix-Game 2.0: An Open-Source, Real-Time, and Streaming Interactive World Model
<div style="display: flex; justify-content: center; gap: 10px;">
<a href="https://github.com/SkyworkAI/Matrix-Game">
<img src="https://img.shields.io/badge/GitHub-100000?style=flat&logo=github&logoColor=white" alt="GitHub">
</a>
<a href="https://github.com/SkyworkAI/Matrix-Game/blob/main/Matrix-Game-2/assets/pdf/report.pdf">
<img src="https://img.shields.io/badge/arXiv-Report-b31b1b?style=flat&logo=arxiv&logoColor=white" alt="report">
</a>
<a href="https://matrix-game-v2.github.io/">
<img src="https://img.shields.io/badge/Project%20Page-grey?style=flat&logo=huggingface&color=FFA500" alt="Project Page">
</a>
</div>
## 📝 Overview
**Matrix-Game-2.0（1.8B）** is an interactive world model generates long videos on-the-fly via few-step auto-regressive diffusion
## ✨ Key Features
- 🚀 **Feature 1**: **Real-Time Distillation** Efficient few-step diffusion for streaming video synthesis at 25 FPS, producing minute-level, high-fidelity videos across complex environments with ultra-fast speed.
- 🖱️ **Feature 2**: **Precise Action Injection** A mouse/keyboard-to-frame module that embeds user inputs as direct interactions, enabling frame-level control and dynamic response in generated videos.
- 🎬 **Feature 3**: **Massive Interactive Data Pipeline** A scalable production system for Unreal Engine & GTA5 that generates ~1350 hours of high-quality interactive video data, covering diverse scenes with frame-level realism.
## 🔥 Latest Updates
* [2025-08] 🎉 Initial release of Matrix-Game-2.0 Model
## Model Overview
**Matrix-Game-2.0（1.8B）** is derived from the Wan. By removing the text branch and adding action modules, the model predicts next frames only from visual contents and corresponding actions.
## 📈 Performance Comparison
### GameWorld Score Benchmark Comparison
| Model | Image Quality ↑ | Aesthetic Quality ↑ | Temporal Cons. ↑ | Motion Smooth. ↑ | Keyboard Acc. ↑ | Mouse Acc. ↑ | Object Cons. | Scenario Cons.|
|-----------|------------------|-------------|-------------------|-------------------|------------------|---------------|-------------|-------------|
| Oasis | 0.27 | 0.27 | 0.82 | **0.99** | 0.73 | 0.56 | 0.18 | **0.84** |
| **Ours** | **0.61** | **0.50** | **0.94** | 0.98 | **0.91** | **0.95** | **0.64** | 0.80 |
**Metric Descriptions**:
- **Image Quality** / **Aesthetic**: Visual fidelity and perceptual appeal of generated frames
- **Temporal Consistency** / **Motion Smoothness**: Temporal coherence and smoothness between frames
- **Keyboard Accuracy** / **Mouse Accuracy**: Accuracy in following user control signals
- **Object Consistency**: Geometric stability and consistency of objects over time
- **Scenario Consistency**: Scenario consistency over time
Please check our [GameWorld](https://github.com/SkyworkAI/Matrix-Game/tree/main/GameWorldScore) benchmark for detailed implementation.
## 🚀 Quick Start
```
# clone the repository:
git clone https://github.com/SkyworkAI/Matrix-Game-2.0
cd Matrix-Game-2.0
# install dependencies:
pip install -r requirements.txt
python setup.py develop
# inference
python inference.py \
--config_path configs/inference_yaml/{your-config}.yaml \
--checkpoint_path {path-to-the-checkpoint} \
--img_path {path-to-the-input-image} \
--output_folder outputs \
--num_output_frames 150 \
--seed 42 \
--pretrained_model_path {path-to-the-vae-folder}
# inference streaming
python inference_streaming.py \
--config_path configs/inference_yaml/{your-config}.yaml \
--checkpoint_path {path-to-the-checkpoint} \
--output_folder outputs \
--seed 42 \
--pretrained_model_path {path-to-the-vae-folder}
```
## ⭐ Acknowledgements
We would like to express our gratitude to:
- [Diffusers](https://github.com/huggingface/diffusers) for their excellent diffusion model framework
- [SkyReels-V2](https://github.com/SkyworkAI/SkyReels-V2) for their strong base model
- [Self-Forcing](https://github.com/guandeh17/Self-Forcing) for their excellent work
- [MineRL](https://github.com/minerllabs/minerl) for their excellent gym framework
- [Video-Pre-Training](https://github.com/openai/Video-Pre-Training) for their accurate Inverse Dynamics Model
- [GameFactory](https://github.com/KwaiVGI/GameFactory) for their idea of action control module
We are grateful to the broader research community for their open exploration and contributions to the field of interactive world generation.
## 📎 Citation
If you find this project useful, please cite our paper:
```bibtex
xxx
``` |