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Action Unit Detection
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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.
<span style="color:grey; opacity: 0.6">( Image credit: AU R-CNN )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Face-LLaVA: Facial Expression and Attribute Understanding through Instruction Tuning
AU-TTT: Vision Test-Time Training model for Facial Action Unit Detection
Detecting Localized Deepfake Manipulations Using Action Unit-Guided Video Representations
Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection
Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding Sample
Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit
Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency
Affective Behavior Analysis using Task-adaptive and AU-assisted Graph Network
Multi-Task Learning for Affect Analysis
Task-adaptive Q-Face
AUD-TGN: Advancing Action Unit Detection with Temporal Convolution and GPT-2 in Wild Audiovisual Contexts
Leveraging Synthetic Data for Generalizable and Fair Facial Action Unit Detection
Contrastive Learning of Person-independent Representations for Facial Action Unit Detection
The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition
Learning Contrastive Feature Representations for Facial Action Unit Detection
Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyond
Boosting Facial Action Unit Detection Through Jointly Learning Facial Landmark Detection and Domain Separation and Reconstruction
FG-Net: Facial Action Unit Detection with Generalizable Pyramidal Features
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
Occlusion Aware Student Emotion Recognition based on Facial Action Unit Detection
Fighting over-fitting with quantization for learning deep neural networks on noisy labels
Multi-modal Facial Action Unit Detection with Large Pre-trained Models for the 5th Competition on Affective Behavior Analysis in-the-wild
ABAW : Facial Expression Recognition in the wild
EmotiEffNet Facial Features in Uni-task Emotion Recognition in Video at ABAW-5 competition
Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detection
Self-supervised Facial Action Unit Detection with Region and Relation Learning
Fighting noise and imbalance in Action Unit detection problems
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challenges
Uncertain Facial Expression Recognition via Multi-task Assisted Correction
FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection
Facial Action Unit Detection and Intensity Estimation from Self-supervised Representation
Global-to-local Expression-aware Embeddings for Facial Action Unit Detection
Multimodal Channel-Mixing: Channel and Spatial Masked AutoEncoder on Facial Action Unit Detection
Affective Behavior Analysis using Action Unit Relation Graph and Multi-task Cross Attention
ABAW: Learning from Synthetic Data & Multi-Task Learning Challenges
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