Skywork/Matrix-Game 已完整同步
Matrix-Game: Interactive World Foundation Model
📝 Overview
Matrix-Game is a 17B-parameter interactive world foundation model for controllable game world generation.
✨ Key Features
- 🎯 Feature 1: Interactive Generation. A diffusion-based image-to-world model that generates high-quality videos conditioned on keyboard and mouse inputs, enabling fine-grained control and dynamic scene evolution.
- 🚀 Feature 2: GameWorld Score. A comprehensive benchmark for evaluating Minecraft world models across four key dimensions, including visual quality, temporal quality, action controllability, and physical rule understanding.
- 💡 Feature 3: Matrix-Game Dataset A large-scale Minecraft dataset with fine-grained action annotations, supporting scalable training for interactive and physically grounded world modeling.
🔥 Latest Updates
- [2025-05] 🎉 Initial release of Matrix-Game Model
🚀 Performance Comparison
GameWorld Score Benchmark Comparison
| Model | Image Quality ↑ | Aesthetic Quality ↑ | Temporal Cons. ↑ | Motion Smooth. ↑ | Keyboard Acc. ↑ | Mouse Acc. ↑ | Object Cons. | Scenario Cons. |
|---|---|---|---|---|---|---|---|---|
| Oasis | 0.65 | 0.48 | 0.94 | 0.98 | 0.77 | 0.56 | 0.56 | 0.86 |
| MineWorld | 0.69 | 0.47 | 0.95 | 0.98 | 0.86 | 0.64 | 0.51 | 0.92 |
| Ours | 0.72 | 0.49 | 0.97 | 0.98 | 0.95 | 0.95 | 0.76 | 0.93 |
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 benchmark for detailed implementation.
Human Evaluation
Human Win Rate
Double-blind human evaluation by two independent groups across four key dimensions: Overall Quality, Controllability, Visual Quality, and Temporal Consistency.
Scores represent the percentage of pairwise comparisons in which each method was preferred. Matrix-Game consistently outperforms prior models across all metrics and both groups.
🚀 Quick Start
# clone the repository:
git clone https://github.com/SkyworkAI/Matrix-Game.git
cd Matrix-Game
# install dependencies:
pip install -r requirements.txt
# install apex and FlashAttention-3
# Our project also depends on [apex](https://github.com/NVIDIA/apex) and [FlashAttention-3](https://github.com/Dao-AILab/flash-attention)
# inference
bash run_inference.sh
⭐ Acknowledgements
We would
29 个文件
浏览文件数据集版权信息
本数据集的许可证为 MIT License。如有违反相关条款,请联系 WEHUB,我们将及时处理。 查看许可证
通过 WeHub CLI 下载当前数据集快照。下列命令会固定为当前页面展示的数据版本(如果页面提供版本)。文件字节由本机直连存储下载,浏览器不会签发或保存下载链接。
前置要求
需要 Node.js 18 及以上,以及 npm(或 npx)。
1. 安装 CLI
npm install -g wehub-cli@latest
2. 下载此数据集
wehub datasets download ds_ext_2916_df70f68190 --revision 6de128116624c07e6ab3ca341978e3e582b67638 --output ./ds_ext_2916_df70f68190
若中断或部分失败,在同一目录重新执行同一命令即可续传。默认会校验 SHA-256。
免全局安装
npx --yes wehub-cli@latest datasets download ds_ext_2916_df70f68190 --revision 6de128116624c07e6ab3ca341978e3e582b67638 --output ./ds_ext_2916_df70f68190
高级选项
以下为 wehub datasets download 已支持的参数示例:
强制重新下载,不复用已校验的本地文件
wehub datasets download ds_ext_2916_df70f68190 --revision 6de128116624c07e6ab3ca341978e3e582b67638 --output ./ds_ext_2916_df70f68190 --overwrite
仅包含匹配路径
wehub datasets download ds_ext_2916_df70f68190 --revision 6de128116624c07e6ab3ca341978e3e582b67638 --output ./ds_ext_2916_df70f68190 --include "*.jsonl"
排除匹配路径
wehub datasets download ds_ext_2916_df70f68190 --revision 6de128116624c07e6ab3ca341978e3e582b67638 --output ./ds_ext_2916_df70f68190 --exclude "*.md"
提高并发下载数
wehub datasets download ds_ext_2916_df70f68190 --revision 6de128116624c07e6ab3ca341978e3e582b67638 --output ./ds_ext_2916_df70f68190 --jobs 8
完整帮助:wehub datasets download --help