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K
ホーム
SOTA
Facial Expression Recognition
Facial Expression Recognition On Fer 1
Facial Expression Recognition On Fer 1
評価指標
Accuracy
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
Accuracy
Paper Title
Repository
DDAMFN
90.74
A Dual-Direction Attention Mixed Feature Network for Facial Expression Recognition
ViT-base
88.91
Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformers
-
FER-VT
90.04
Facial expression recognition with grid-wise attention and visual transformer
LResNet50E-IR
89.257
Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition
-
Ensemble with Shared Representations (ESR-9)
87.15
Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks
EAC
89.64
Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
QCS
91.85
QCS: Feature Refining from Quadruplet Cross Similarity for Facial Expression Recognition
Vit-base + MAE
90.18
Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformers
-
ViT-tiny
88.56
Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformers
-
ResNet18 Dense Architecture
91.41
Real Time Emotion Analysis Using Deep Learning for Education, Entertainment, and Beyond
-
GReFEL
93.09
GReFEL: Geometry-Aware Reliable Facial Expression Learning under Bias and Imbalanced Data Distribution
-
KTN
90.49
Adaptively Learning Facial Expression Representation via C-F Labels and Distillation
-
Local Learning Deep + BOW
87.76
Local Learning with Deep and Handcrafted Features for Facial Expression Recognition
-
PAtt-Lite
95.55
PAtt-Lite: Lightweight Patch and Attention MobileNet for Challenging Facial Expression Recognition
-
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