FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation

Author:

Yan Yanfu,Lu Ke,Xue Jian,Gao Pengcheng,Lyu Jiayi

Publisher

IEEE

Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automatic Generation of Robot Facial Expressions with Preferences;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

2. Spatio-Temporal Graph Analytics on Secondary Affect Data for Improving Trustworthy Emotional AI;IEEE Transactions on Affective Computing;2023

3. From Local to Holistic: Self-supervised Single Image 3D Face Reconstruction Via Multi-level Constraints;2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2022-10-23

4. FEAFA+: an extended well-annotated dataset for facial expression analysis and 3D facial animation;Fourteenth International Conference on Digital Image Processing (ICDIP 2022);2022-10-12

5. A Local-Global Metric Learning Method for Facial Expression Animation;2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR);2022-08

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