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Action Unit Detection

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 )

Papers

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Showing 1–50 of 108 papers

TitleStatusHype
Multitask Emotion Recognition with Incomplete LabelsCode1
FG-Net: Facial Action Unit Detection with Generalizable Pyramidal FeaturesCode1
JAA-Net: Joint Facial Action Unit Detection and Face Alignment via Adaptive AttentionCode1
EmotiEffNet Facial Features in Uni-task Emotion Recognition in Video at ABAW-5 competitionCode0
A Compact Embedding for Facial Expression SimilarityCode0
Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding SampleCode0
Deep Region and Multi-Label Learning for Facial Action Unit DetectionCode0
Video-Based Frame-Level Facial Analysis of Affective Behavior on Mobile Devices Using EfficientNetsCode0
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit DetectionCode0
Learning Contrastive Feature Representations for Facial Action Unit DetectionCode0
Self-Supervised Representation Learning From Videos for Facial Action Unit DetectionCode0
Unconstrained Facial Action Unit Detection via Latent Feature DomainCode0
Deep Adaptive Attention for Joint Facial Action Unit Detection and Face AlignmentCode0
AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit DetectionCode0
Rethinking Affect Analysis: A Protocol for Ensuring Fairness and ConsistencyCode0
Multi-View Dynamic Facial Action Unit DetectionCode0
An Empirical Study of Dimensional Reduction Techniques for Facial Action Units Detection—0
Cross-subject Action Unit Detection with Meta Learning and Transformer-based Relation Modeling—0
An Attention-based Method for Action Unit Detection at the 3rd ABAW Competition—0
Analysing Affective Behavior in the second ABAW2 Competition—0
Computational efficient deep neural network with difference attention maps for facial action unit detection—0
Analysing Affective Behavior in the First ABAW 2020 Competition—0
Accurate Facial Parts Localization and Deep Learning for 3D Facial Expression Recognition—0
Confidence Preserving Machine for Facial Action Unit Detection—0
Confidence-Weighted Local Expression Predictions for Occlusion Handling in Expression Recognition and Action Unit detection—0
Contrastive Learning of Person-independent Representations for Facial Action Unit Detection—0
ABAW: Learning from Synthetic Data & Multi-Task Learning Challenges—0
Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection—0
Choose Settings Carefully: Comparing Action Unit detection at Different Settings Using a Large-Scale Dataset—0
Boosting Facial Action Unit Detection Through Jointly Learning Facial Landmark Detection and Domain Separation and Reconstruction—0
Affective Behavior Analysis using Task-adaptive and AU-assisted Graph Network—0
Biomechanics-Guided Facial Action Unit Detection Through Force Modeling—0
Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit—0
Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework—0
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challenges—0
Expression Empowered ResiDen Network for Facial Action Unit Detection—0
Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace—0
AU-TTT: Vision Test-Time Training model for Facial Action Unit Detection—0
Face-LLaVA: Facial Expression and Attribute Understanding through Instruction Tuning—0
Facial Action Unit Detection and Intensity Estimation from Self-supervised Representation—0
Exploiting Semantic Embedding and Visual Feature for Facial Action Unit Detection—0
Facial Action Unit Detection on ICU Data for Pain Assessment—0
Facial Action Unit Detection using 3D Facial Landmarks—0
Facial Action Unit Detection Using Attention and Relation Learning—0
Facial Action Unit Detection With Transformers—0
Facial movement synergies and Action Unit detection from distal wearable Electromyography and Computer Vision—0
FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection—0
Fast and Effective Adaptation of Facial Action Unit Detection Deep Model—0
Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusing—0
EAC-Net: A Region-based Deep Enhancing and Cropping Approach for Facial Action Unit Detection—0
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