Add pipeline tag and improve model card

#2
by nielsr HF Staff - opened
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  1. README.md +22 -7
README.md CHANGED
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  ---
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  license: mit
 
 
 
 
 
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  ---
 
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  # SCAIL: Towards Studio-Grade Character Animation via In-Context Learning of 3D-Consistent Pose Representations
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  <div align="center">
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- <a href="https://arxiv.org/abs/2512.05905">
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- <img src="https://img.shields.io/badge/πŸ“–%20arXiv-2512.05905-red">
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  </a>
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  <a href="https://teal024.github.io/SCAIL/">
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  <img src="https://img.shields.io/badge/🌐%20Project%20Page-green">
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  </div>
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- This repository contains the model weights for **SCAIL (Studio-Grade Character Animation via In-Context Learning)**, a framework that enables high-fidelity character animation under diverse and challenging conditions, including large motion variations, stylized characters, and multi-character interactions.
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- ## πŸ”Ž Project Page
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- Check our model architecture design, our video demo, as well as more comparisons against other baselines at [this link](https://teal024.github.io/SCAIL/), more creative examples will be added to the gallery soon.
 
 
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  ## πŸ“‹ Note
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- This repository only contains the model weights for the SCAIL model, for model inference and our plan, please refer to the [official repository](https://github.com/teal024/SCAIL-Official). For pose extraction, please refer to the [SCAIL-Pose](https://github.com/teal024/SCAIL-Pose).
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  ## πŸ“„ Citation
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@@ -33,8 +45,11 @@ If you find this work useful in your research, please cite:
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  ```bibtex
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  @article{yan2025scail,
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  title={SCAIL: Towards Studio-Grade Character Animation via In-Context Learning of 3D-Consistent Pose Representations},
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- author={Yan, Wenhao and Ye, Sheng and Yang, Zhuoyi and Teng, Jiayan and Dong, ZhenHui and Wen, Kairui and Gu, Xiaotao and Liu, Yong-Jin and Tang, Jie},
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  journal={arXiv preprint arXiv:2512.05905},
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  year={2025}
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  }
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  ```
 
 
 
 
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  ---
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  license: mit
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+ pipeline_tag: image-to-video
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+ tags:
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+ - character-animation
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+ - 3d-pose
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+ - motion-transfer
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  ---
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+
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  # SCAIL: Towards Studio-Grade Character Animation via In-Context Learning of 3D-Consistent Pose Representations
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  <div align="center">
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+ <a href="https://huggingface.co/papers/2512.05905">
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+ <img src="https://img.shields.io/badge/πŸ“–%20Paper-2512.05905-red">
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  </a>
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  <a href="https://teal024.github.io/SCAIL/">
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  <img src="https://img.shields.io/badge/🌐%20Project%20Page-green">
 
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  </div>
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+ **SCAIL** (Studio-grade Character Animation via In-context Learning) is a framework designed to achieve high-fidelity character animation that meets studio standards. It addresses challenges in preserving structural fidelity and temporal consistency during motion transfer, especially in complex scenarios involving large motions and multi-character interactions.
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+ Key features include:
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+ - **3D-Consistent Pose Representations**: Provides a robust and flexible motion signal while preventing identity leakage.
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+ - **Full-Context Pose Injection**: Enables effective spatio-temporal reasoning over entire motion sequences within a diffusion-transformer.
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+ - **Studio-Grade Quality**: Trained on a curated data pipeline to ensure diversity and quality.
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+ This repository contains the model weights for the **SCAIL-Preview (14B)** model.
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+
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+ ## πŸ”Ž Project Page
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+ Check the model architecture design, video demos, and comparisons against other baselines at the [official project page](https://teal024.github.io/SCAIL/).
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  ## πŸ“‹ Note
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+ This repository contains the model weights for the SCAIL model. For model inference, environment setup, and the roadmap, please refer to the [official repository](https://github.com/teal024/SCAIL-Official). For pose extraction tools, refer to [SCAIL-Pose](https://github.com/teal024/SCAIL-Pose).
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  ## πŸ“„ Citation
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  ```bibtex
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  @article{yan2025scail,
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  title={SCAIL: Towards Studio-Grade Character Animation via In-Context Learning of 3D-Consistent Pose Representations},
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+ author={Yan, Wenhao and Ye, Sheng English and Yang, Zhuoyi and Teng, Jiayan and Dong, ZhenHui and Wen, Kairui and Gu, Xiaotao and Liu, Yong-Jin and Tang, Jie},
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  journal={arXiv preprint arXiv:2512.05905},
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  year={2025}
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  }
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  ```
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+
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+ ## πŸ‘₯ Authors
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+ [Wenhao Yan](https://huggingface.co/wenhaoyan77), Sheng Ye, Zhuoyi Yang, [Jiayan Teng](https://huggingface.co/tengjiayan), ZhenHui Dong, [Kairui Wen](https://huggingface.co/SKearbvaanl), [Xiaotao Gu](https://huggingface.co/xgeric), Yong-Jin Liu, [Jie Tang](https://huggingface.co/jerytang).