Improve model card: add pipeline_tag, library_name, link project page and update images
#4
by
nielsr
HF Staff
- opened
README.md
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---
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license: mit
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language:
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- en
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base_model:
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- Skywork/Matrix-Game
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---
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<!-- markdownlint-disable first-line-h1 -->
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<!-- markdownlint-disable html -->
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@@ -17,6 +20,9 @@ base_model:
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<a href="https://arxiv.org/pdf/2506.18701">
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<img src="https://img.shields.io/badge/arXiv-Report-b31b1b?style=flat&logo=arxiv&logoColor=white" alt="arXiv">
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</a>
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</div>
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@@ -37,24 +43,25 @@ base_model:
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## π Performance Comparison
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### GameWorld Score Benchmark Comparison
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| Model | Image Quality β | Aesthetic Quality β | Temporal Cons. β | Motion Smooth. β | Keyboard Acc. β | Mouse Acc. β |
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| Oasis | 0.65 | 0.48 | 0.94 | **0.98** | 0.77 | 0.56 | 0.56 |
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| MineWorld | 0.69 | 0.47 | 0.95 | **0.98** | 0.86 | 0.64 | 0.51 |
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| **Ours** | **0.72** | **0.49** | **0.97** | **0.98** | **0.95** | **0.95** | **0.76** |
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**Metric Descriptions**:
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- **Image Quality** / **Aesthetic**: Visual fidelity and perceptual appeal of generated frames
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- **Temporal Consistency** / **Motion Smoothness**: Temporal coherence and smoothness between frames
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- **Keyboard Accuracy** / **Mouse Accuracy**: Accuracy in following user control signals
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- **
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Please check our [GameWorld](https://github.com/SkyworkAI/Matrix-Game/tree/main/GameWorldScore) benchmark for detailed implementation.
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### Human Evaluation
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> Double-blind human evaluation by two independent groups across four key dimensions: **Overall Quality**, **Controllability**, **Visual Quality**, and **Temporal Consistency**.
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> 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.
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---
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base_model:
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- Skywork/Matrix-Game
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language:
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- en
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license: mit
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library_name: diffusers
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pipeline_tag: image-to-video
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---
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<!-- markdownlint-disable first-line-h1 -->
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<!-- markdownlint-disable html -->
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<!-- markdownlint-disable no-duplicate-header -->
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<a href="https://arxiv.org/pdf/2506.18701">
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<img src="https://img.shields.io/badge/arXiv-Report-b31b1b?style=flat&logo=arxiv&logoColor=white" alt="arXiv">
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</a>
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<a href="https://matrix-game-homepage.github.io/">
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<img src="https://img.shields.io/badge/Project%20Page-grey?style=flat&logo=huggingface&color=FFA500" alt="Project Page">
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</a>
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</div>
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## π Performance Comparison
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### GameWorld Score Benchmark Comparison
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| Model | Image Quality β | Aesthetic Quality β | Temporal Cons. β | Motion Smooth. β | Keyboard Acc. β | Mouse Acc. β | Object Cons. | Scenario Cons.|
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|-----------|------------------|-------------|-------------------|-------------------|------------------|---------------|-------------|-------------|
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| Oasis | 0.65 | 0.48 | 0.94 | **0.98** | 0.77 | 0.56 | 0.56 | 0.86 |
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| MineWorld | 0.69 | 0.47 | 0.95 | **0.98** | 0.86 | 0.64 | 0.51 | 0.92 |
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| **Ours** | **0.72** | **0.49** | **0.97** | **0.98** | **0.95** | **0.95** | **0.76** | **0.93** |
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**Metric Descriptions**:
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- **Image Quality** / **Aesthetic**: Visual fidelity and perceptual appeal of generated frames
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- **Temporal Consistency** / **Motion Smoothness**: Temporal coherence and smoothness between frames
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- **Keyboard Accuracy** / **Mouse Accuracy**: Accuracy in following user control signals
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- **Object Consistency**: Geometric stability and consistency of objects over time
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- **Scenario Consistency**: Scenario consistency over time
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Please check our [GameWorld](https://github.com/SkyworkAI/Matrix-Game/tree/main/GameWorldScore) benchmark for detailed implementation.
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### Human Evaluation
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> Double-blind human evaluation by two independent groups across four key dimensions: **Overall Quality**, **Controllability**, **Visual Quality**, and **Temporal Consistency**.
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> 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.
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