Conditional adversarial synthesis of 3D facial action unit
Employing deep learning-based approaches for fine-grained facial expression analysis, such as those involving the estimation of Action Unit (AU) intensities, is difficult due to the lack of a large-scale dataset of real faces with sufficiently diverse AU labels for training. In this paper, we consid...
Saved in:
Main Authors: | Liu, Zhilei, Song, Guoxian, Cai, Jianfei, Cham, Tat-Jen, Zhang, Juyong |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/138268 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
GeoConv: geodesic guided convolution for facial action unit recognition
by: Chen, Yuedong, et al.
Published: (2023) -
Stress Detection in Video Feed: Utilizing Facial Action Units as Indicators in Various Machine Learning Algorithms
by: Llanes, Rizzah Grace, et al.
Published: (2022) -
Unconstrained facial action unit detection via latent feature domain
by: Shao, Zhiwen, et al.
Published: (2023) -
Recovering facial reflectance and geometry from multi-view images
by: Song, Guoxian, et al.
Published: (2023) -
Facial action unit detection using attention and relation learning
by: Shao, Zhiwen, et al.
Published: (2022)