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Facial Action Unit Detection

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 )

Papers

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Showing 1–50 of 96 papers

TitleStatusHype
FG 2025 TrustFAA: the First Workshop on Towards Trustworthy Facial Affect Analysis: Advancing Insights of Fairness, Explainability, and Safety (TrustFAA)—0
AU-TTT: Vision Test-Time Training model for Facial Action Unit Detection—0
Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection—0
Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding SampleCode0
Towards Unified Facial Action Unit Recognition Framework by Large Language Models—0
Towards End-to-End Explainable Facial Action Unit Recognition via Vision-Language Joint Learning—0
Norface: Improving Facial Expression Analysis by Identity NormalizationCode1
Representation Learning and Identity Adversarial Training for Facial Behavior UnderstandingCode2
Multi-scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units RecognitionCode1
AUD-TGN: Advancing Action Unit Detection with Temporal Convolution and GPT-2 in Wild Audiovisual Contexts—0
Leveraging Synthetic Data for Generalizable and Fair Facial Action Unit Detection—0
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective ComputingCode1
AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit DetectorsCode2
Contrastive Learning of Person-independent Representations for Facial Action Unit Detection—0
Learning Contrastive Feature Representations for Facial Action Unit DetectionCode0
Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyond—0
Boosting Facial Action Unit Detection Through Jointly Learning Facial Landmark Detection and Domain Separation and Reconstruction—0
FG-Net: Facial Action Unit Detection with Generalizable Pyramidal FeaturesCode1
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit DetectionCode0
Occlusion Aware Student Emotion Recognition based on Facial Action Unit Detection—0
Fighting over-fitting with quantization for learning deep neural networks on noisy labels—0
Multi-modal Facial Action Unit Detection with Large Pre-trained Models for the 5th Competition on Affective Behavior Analysis in-the-wild—0
Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detection—0
Self-supervised Facial Action Unit Detection with Region and Relation Learning—0
ReactioNet: Learning High-Order Facial Behavior from Universal Stimulus-Reaction by Dyadic Relation Reasoning—0
Biomechanics-Guided Facial Action Unit Detection Through Force Modeling—0
FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection—0
Facial Action Unit Detection and Intensity Estimation from Self-supervised Representation—0
Global-to-local Expression-aware Embeddings for Facial Action Unit Detection—0
Multimodal Channel-Mixing: Channel and Spatial Masked AutoEncoder on Facial Action Unit Detection—0
Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit RecognitionCode2
Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition—0
Weakly Supervised Regional and Temporal Learning for Facial Action Unit Recognition—0
Facial Action Unit Recognition Based on Transfer Learning—0
Multi-modal Multi-label Facial Action Unit Detection with Transformer—0
Facial Action Unit Recognition With Multi-models Ensembling—0
Multi-Order Networks for Action Unit Detection—0
Knowledge-Driven Self-Supervised Representation Learning for Facial Action Unit Recognition—0
Self-Supervised Regional and Temporal Auxiliary Tasks for Facial Action Unit Recognition—0
Facial Action Unit Detection With Transformers—0
Exploiting Semantic Embedding and Visual Feature for Facial Action Unit Detection—0
Hybrid Message Passing With Performance-Driven Structures for Facial Action Unit Detection—0
Exploring Adversarial Learning for Deep Semi-Supervised Facial Action Unit Recognition—0
Meta Auxiliary Learning for Facial Action Unit Detection—0
Pre-training strategies and datasets for facial representation learningCode1
Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework—0
DeepFN: Towards Generalizable Facial Action Unit Recognition with Deep Face Normalization—0
Multi-Level Adaptive Region of Interest and Graph Learning for Facial Action Unit Recognition—0
Automated Detection of Equine Facial Action UnitsCode0
PIAP-DF: Pixel-Interested and Anti Person-Specific Facial Action Unit Detection Net With Discrete Feedback Learning—0
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