SOTAVerified

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 76–100 of 108 papers

TitleStatusHype
Modeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection—0
Multi-Conditional Latent Variable Model for Joint Facial Action Unit Detection—0
Multi-Label Class Balancing Algorithm for Action Unit Detection—0
Multi-label Learning with Missing Values using Combined Facial Action Unit Datasets—0
Multi-label Transformer for Action Unit Detection—0
Multi-modal Facial Action Unit Detection with Large Pre-trained Models for the 5th Competition on Affective Behavior Analysis in-the-wild—0
Multi-Modal Learning for AU Detection Based on Multi-Head Fused Transformers—0
Multimodal Channel-Mixing: Channel and Spatial Masked AutoEncoder on Facial Action Unit Detection—0
Multi-modal Multi-label Facial Action Unit Detection with Transformer—0
Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis—0
Multi-Order Networks for Action Unit Detection—0
Affective Behavior Analysis using Action Unit Relation Graph and Multi-task Cross Attention—0
Multi-Task Learning for Affect Analysis—0
Objective Class-based Micro-Expression Recognition through Simultaneous Action Unit Detection and Feature Aggregation—0
Occlusion Aware Student Emotion Recognition based on Facial Action Unit Detection—0
PIAP-DF: Pixel-Interested and Anti Person-Specific Facial Action Unit Detection Net With Discrete Feedback Learning—0
ReactioNet: Learning High-Order Facial Behavior from Universal Stimulus-Reaction by Dyadic Relation Reasoning—0
Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection—0
Relative Facial Action Unit Detection—0
Selective Transfer Machine for Personalized Facial Action Unit Detection—0
Self-supervised Facial Action Unit Detection with Region and Relation Learning—0
Facial Action Unit Detection via Adaptive Attention and Relation—0
Deep Region and Multi-Label Learning for Facial Action Unit DetectionCode0
Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding SampleCode0
AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit DetectionCode0
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