Facial Expression Recognition On Affectnet

Métriques

Accuracy (8 emotion)

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy (8 emotion)	Paper Title	Repository
VGG-FACE	60.40	Deep Neural Network Augmentation: Generating Faces for Affect Analysis	-
PSR (VGG-16)	60.68	Pyramid With Super Resolution for In-the-Wild Facial Expression Recognition
EfficientFace	59.89	Robust Lightweight Facial Expression Recognition Network with Label Distribution Training
ResEmoteNet	-	ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognition
SL (B0)	60.34	Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation	-
Vit-base + MAE	62.42	Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformers	-
FerNeXt	-	FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel Attention
CNNs and BOVW + local SVM	59.58	Local Learning with Deep and Handcrafted Features for Facial Expression Recognition	-
Distilled student	61.60	Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition	-
LFNSB	63.12	A Lightweight Model Enhancing Facial Expression Recognition with Spatial Bias and Cosine-Harmony Loss
PAENet	-	Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning
Ad-Corre	-	Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the Wild	-
Facial Motion Prior Network	-	Facial Motion Prior Networks for Facial Expression Recognition
Ada-DF	-	A Dual-Branch Adaptive Distribution Fusion Framework for Real-World Facial Expression Recognition
POSTER++	63.77	POSTER++: A simpler and stronger facial expression recognition network
SL + SSL puzzling (B0)	61.09	Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation	-
Ensemble with Shared Representations (ESR-9)	59.3	Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks
S2D	63.06	From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos
EAC	-	Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
QCS	64.4	QCS: Feature Refining from Quadruplet Cross Similarity for Facial Expression Recognition

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