Facial Action Unit Detection
17 papers with code • 2 benchmarks • 4 datasets
Facial action unit detection is the task of detecting action units from a video of a face - for example, lip tightening and cheek raising.
( Image credit: Self-supervised Representation Learning from Videos for Facial Action Unit Detection )
Libraries
Use these libraries to find Facial Action Unit Detection models and implementations
DISFA
BP4D
CANDOR Corpus
Thermal Face Database
Most implemented papers
Self-Supervised Representation Learning From Videos for Facial Action Unit Detection
In this paper, we aim to learn discriminative representation for facial action unit (AU) detection from large amount of videos without manual annotations.
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition
nxsEdson/MLCR
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NeurIPS 2019
In this work, we propose a semi-supervised approach for AU recognition utilizing a large number of web face images without AU labels and a relatively small face dataset with AU annotations inspired by the co-training methods.
J$\hat{\text{A}}$A-Net: Joint Facial Action Unit Detection and Face Alignment via Adaptive Attention
Moreover, to extract precise local features, we propose an adaptive attention learning module to refine the attention map of each AU adaptively.
Automated Detection of Equine Facial Action Units
ZhenghLi/Automated-Detection-of-Equine-Facial-Action-Units
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To automate parts of this process, we propose a Deep Learning-based method to detect EquiFACS units automatically from images.
FG-Net: Facial Action Unit Detection with Generalizable Pyramidal Features
ihp-lab/fg-net
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The proposed FG-Net achieves a strong generalization ability for heatmap-based AU detection thanks to the generalizable and semantic-rich features extracted from the pre-trained generative model.
Learning Contrastive Feature Representations for Facial Action Unit Detection
To address the challenge posed by noisy AU labels, we augment the supervised signal through the introduction of a self-supervised signal.
AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors
Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic.
