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Facial Action Unit Detection On Bp4D

Metrics

Average F1

Results

Performance results of various models on this benchmark

		Paper Title	Repository
Norface	69.3	Norface: Improving Facial Expression Analysis by Identity Normalization
FMAE-IAT	67.1	Representation Learning and Identity Adversarial Training for Facial Behavior Understanding
FMAE	66.6	Representation Learning and Identity Adversarial Training for Facial Behavior Understanding
MDHRD	66.6	Multi-scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units Recognition
AUFormer	66.2	AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection	65.6	Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
Multi-dimensional Edge Feature-based AU Relation Graph (Swin-B)	65.5	Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition
Multi-dimensional Edge Feature-based AU Relation Graph (ResNet 50)	64.7	Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition
Multi-View Dynamic Facial Action Unit Detection	63.0	Multi-View Dynamic Facial Action Unit Detection
Swin-B	62.6	Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition
JAA-Net	60.0	Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment
ResNet 50	59.1	Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition
DRML	48.3	Deep Region and Multi-Label Learning for Facial Action Unit Detection	-

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Facial Action Unit Detection On Bp4D | SOTA | HyperAI