Action Unit Detection
16 papers with code • 1 benchmarks • 3 datasets
Action unit detection is the task of detecting action units from a video - for example, types of facial action units (lip tightening, cheek raising) from a video of a face.
( Image credit: AU R-CNN )
Libraries
Use these libraries to find Action Unit Detection models and implementations
Aff-Wild
BP4D
4DFAB
Most implemented papers
Multitask Emotion Recognition with Incomplete Labels
wtomin/Multitask-Emotion-Recognition-with-Incomplete-Labels
•
•
We use the soft labels and the ground truth to train the student model.
Deep Region and Multi-Label Learning for Facial Action Unit Detection
Region learning (RL) and multi-label learning (ML) have recently attracted increasing attentions in the field of facial Action Unit (AU) detection.
A Compact Embedding for Facial Expression Similarity
Most of the existing work on automatic facial expression analysis focuses on discrete emotion recognition, or facial action unit detection.
AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection
(2) We integrate various dynamic models (including convolutional long short-term memory, two stream network, conditional random field, and temporal action localization network) into AU R-CNN and then investigate and analyze the reason behind the performance of dynamic models.
Video-Based Frame-Level Facial Analysis of Affective Behavior on Mobile Devices Using EfficientNets
HSE-asavchenko/face-emotion-recognition
•
•
CVPR Workshop 2022
In this paper, we consider the problem of real-time video-based facial emotion analytics, namely, facial expression recognition, prediction of valence and arousal and detection of action unit points.
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
yuankaishen2001/Self-adjusting-AU
•
•
Anatomically, there are innumerable correlations between AUs, which contain rich information and are vital for AU detection.
Multi-View Dynamic Facial Action Unit Detection
We then move to the novel setup of the FERA 2017 Challenge, in which we propose a multi-view extension of our approach that operates by first predicting the viewpoint from which the video was taken, and then evaluating an ensemble of action unit detectors that were trained for that specific viewpoint.
Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment
ZhiwenShao/JAANet
•
•
ECCV 2018
Facial action unit (AU) detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaningful local features for AU detection.
Unconstrained Facial Action Unit Detection via Latent Feature Domain
ZhiwenShao/ADLD
•
•
Due to the combination of source AU-related information and target AU-free information, the latent feature domain with transferred source label can be learned by maximizing the target-domain AU detection performance.
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.
