CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

Hao Zhu, Wayne Wu, Wentao Zhu, Liming Jiang, Siwei Tang, Li Zhang, Ziwei Liu, Chen Change Loy

ECCV 2022

doi:10.1007/978-3-031-20071-7_38 /eccv/2022/zhu2022eccv-celebvhq/

Abstract

Large-scale datasets played an indispensable role in the recent success of face generation/editing and significantly facilitate the advances of emerging research fields. However, the academic community still lacks a video dataset with diverse facial attribute annotations, which is crucial for face-related video research. In this paper, we propose a large-scale, high-quality, and diverse video dataset, named the High-Quality Celebrity Video Dataset (CelebV-HQ), with rich facial attribute annotations. CelebV-HQ contains 35,666 video clips involving 15,653 identities and 83 manually labeled facial attributes covering appearance, action, and emotion. We conduct a comprehensive analysis in terms of ethnicity, age, brightness, motion smoothness, head pose diversity, and data quality to demonstrate the diversity and temporal coherence of CelebV-HQ. Besides, its versatility and potential are validated on unconditional video generation and video facial attribute editing tasks. Furthermore, we envision the future potential of CelebV-HQ, as well as the new opportunities and challenges it would bring to related research directions.

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Cite

Text

Zhu et al. "CelebV-HQ: A Large-Scale Video Facial Attributes Dataset." Proceedings of the European Conference on Computer Vision (ECCV), 2022. doi:10.1007/978-3-031-20071-7_38

Markdown

[Zhu et al. "CelebV-HQ: A Large-Scale Video Facial Attributes Dataset." Proceedings of the European Conference on Computer Vision (ECCV), 2022.](https://mlanthology.org/eccv/2022/zhu2022eccv-celebvhq/) doi:10.1007/978-3-031-20071-7_38

BibTeX

@inproceedings{zhu2022eccv-celebvhq,
  title     = {{CelebV-HQ: A Large-Scale Video Facial Attributes Dataset}},
  author    = {Zhu, Hao and Wu, Wayne and Zhu, Wentao and Jiang, Liming and Tang, Siwei and Zhang, Li and Liu, Ziwei and Loy, Chen Change},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year      = {2022},
  doi       = {10.1007/978-3-031-20071-7_38},
  url       = {https://mlanthology.org/eccv/2022/zhu2022eccv-celebvhq/}
}