SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformers

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This repo contains Diffusers style model weights for Skyreels A1 models. You can find the inference code on SkyReels-A1 repository.

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Overview of SkyReels-A1 framework. Given an input video sequence and a reference portrait image, we extract facial expression-aware landmarks from the video, which serve as motion descriptors for transferring expressions onto the portrait. Utilizing a conditional video generation framework based on DiT, our approach directly integrates these facial expression-aware landmarks into the input latent space. In alignment with prior research, we employ a pose guidance mechanism constructed within a VAE architecture. This component encodes facial expression-aware landmarks as conditional input for the DiT framework, thereby enabling the model to capture essential low- dimensional visual attributes while preserving the semantic integrity of facial features.

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Some generated results:

Citation

If you find SkyReels-A1 useful for your research, welcome to cite our work using the following BibTeX:

@article{qiu2025skyreels,
  title={SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformers},
  author={Qiu, Di and Fei, Zhengcong and Wang, Rui and Bai, Jialin and Yu, Changqian and Fan, Mingyuan and Chen, Guibin and Wen, Xiang},
  journal={arXiv preprint arXiv:2502.10841},
  year={2025}
}