Facial Expression Recognition (FER)

Facial Expression Recognition (FER) is a computer vision task aimed at identifying and categorizing emotional expressions depicted on a human face. The goal is to automate the process of determining emotions in real-time, by analyzing the various features of a face such as eyebrows, eyes, mouth, and other features, and mapping them to a set of emotions such as anger, fear, surprise, sadness and happiness.

( Image credit: DeXpression )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 251–275 of 492 papers

Title	Date	Tasks	Status
Meta Auxiliary Learning for Facial Action Unit Detection	May 14, 2021	Action Unit DetectionAuxiliary Learning	—Unverified
Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation	May 13, 2021	Emotion RecognitionFacial Emotion Recognition	—Unverified
Deep and Shallow Covariance Feature Quantization for 3D Facial Expression Recognition	May 12, 2021	3D Facial Expression RecognitionFacial Expression Recognition	—Unverified
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study	May 8, 2021	Action Unit DetectionAttribute	—Unverified
CASIA-Face-Africa: A Large-scale African Face Image Database	May 8, 2021	Age EstimationFace Recognition	—Unverified
MAFER: a Multi-resolution Approach to Facial Expression Recognition	May 6, 2021	Face RecognitionFacial Expression Recognition	CodeCode Available
Magnifying Subtle Facial Motions for Effective 4D Expression Recognition	May 5, 2021	Emotion ClassificationFacial Expression Recognition	—Unverified
Landmark-Aware and Part-based Ensemble Transfer Learning Network for Facial Expression Recognition from Static images	Apr 22, 2021	Computational EfficiencyEnsemble Learning	—Unverified
I Only Have Eyes for You: The Impact of Masks On Convolutional-Based Facial Expression Recognition	Apr 16, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Do Deep Neural Networks Forget Facial Action Units? -- Exploring the Effects of Transfer Learning in Health Related Facial Expression Recognition	Apr 15, 2021	Emotion RecognitionFacial Expression Recognition	—Unverified
Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition	Apr 12, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
On the Pitfalls of Learning with Limited Data: A Facial Expression Recognition Case Study	Apr 2, 2021	Data AugmentationDeep Learning	—Unverified
Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition	Apr 1, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	CodeCode Available
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks	Mar 31, 2021	Emotion ClassificationFace Identification	—Unverified
Facial Expression Recognition with Visual Transformers and Attentional Selective Fusion	Mar 31, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Imponderous Net for Facial Expression Recognition in the Wild	Mar 28, 2021	CPUFacial Expression Recognition	—Unverified
Convolutional Neural Network Hyperparameters optimization for Facial Emotion Recognition	Mar 25, 2021	Emotion RecognitionFacial Emotion Recognition	CodeCode Available
Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition	Mar 24, 2021	Arousal EstimationEmotion Recognition	—Unverified
A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition	Mar 23, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Responsible AI: Gender bias assessment in emotion recognition	Mar 21, 2021	Emotion RecognitionFacial Expression Recognition	—Unverified
Learning to Amend Facial Expression Representation via De-albino and Affinity	Mar 18, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	CodeCode Available
Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition	Mar 16, 2021	Deep LearningEmotion Recognition	—Unverified
Towards Fair Affective Robotics: Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition	Mar 15, 2021	Continual LearningFacial Expression Recognition	—Unverified
Detection and Localization of Facial Expression Manipulations	Mar 15, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Domain-Incremental Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition	Mar 15, 2021	Continual LearningFacial Expression Recognition	—Unverified

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All datasets AffectNet RAF-DB FER2013 FER+Acted Facial Expressions In The Wild (AFEW)CK+FERPlus JAFFE SFEW Aff-Wild2 BP4D DISFA

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ResEmoteNet	Accuracy (7 emotion)	72.93	—	Unverified
2	Norface	Accuracy (8 emotion)	68.69	—	Unverified
3	EmoAffectNet	Accuracy (7 emotion)	66.49	—	Unverified
4	Emotion-GCN	Accuracy (7 emotion)	66.46	—	Unverified
5	FaceBehaviorNet	Accuracy (7 emotion)	65.4	—	Unverified
6	Ada-DF	Accuracy (7 emotion)	65.34	—	Unverified
7	EAC	Accuracy (7 emotion)	65.32	—	Unverified
8	PAENet	Accuracy (7 emotion)	65.29	—	Unverified
9	DACL	Accuracy (7 emotion)	65.2	—	Unverified
10	DDAMFN++	Accuracy (8 emotion)	65.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResEmoteNet	Overall Accuracy	94.76	—	Unverified
2	FMAE	Overall Accuracy	93.45	—	Unverified
3	QCS	Overall Accuracy	93.02	—	Unverified
4	Norface	Overall Accuracy	92.97	—	Unverified
5	S2D	Overall Accuracy	92.57	—	Unverified
6	BTN	Overall Accuracy	92.54	—	Unverified
7	GReFEL	Overall Accuracy	92.47	—	Unverified
8	DDAMFN++	Overall Accuracy	92.34	—	Unverified
9	DCJT	Overall Accuracy	92.24	—	Unverified
10	POSTER++	Overall Accuracy	92.21	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EfficientFER	Accuracy	82.47	—	Unverified
2	FERNeXt-SDAFE	Accuracy	81.33	—	Unverified
3	ResEmoteNet	Accuracy	79.79	—	Unverified
4	Ensemble ResMaskingNet with 6 other CNNs	Accuracy	76.82	—	Unverified
5	Mini-ResEmoteNet (A)	Accuracy	76.33	—	Unverified
6	EmoNeXt	Accuracy	76.12	—	Unverified
7	Segmentation VGG-19	Accuracy	75.97	—	Unverified
8	Local Learning Deep+BOW	Accuracy	75.42	—	Unverified
9	LHC-Net	Accuracy	74.42	—	Unverified
10	Residual Masking Network	Accuracy	74.14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PAtt-Lite	Accuracy	95.55	—	Unverified
2	GReFEL	Accuracy	93.09	—	Unverified
3	QCS	Accuracy	91.85	—	Unverified
4	ResNet18 Dense Architecture	Accuracy	91.41	—	Unverified
5	DDAMFN	Accuracy	90.74	—	Unverified
6	KTN	Accuracy	90.49	—	Unverified
7	Vit-base + MAE	Accuracy	90.18	—	Unverified
8	FER-VT	Accuracy	90.04	—	Unverified
9	EAC	Accuracy	89.64	—	Unverified
10	LResNet50E-IR	Accuracy	89.26	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet50	Accuracy(on validation set)	65.5	—	Unverified
2	LResNet50E-IR (5 models with augmentation)	Accuracy(on validation set)	65.5	—	Unverified
3	EAC	Accuracy(on validation set)	65.32	—	Unverified
4	LResNet50E-IR (1 model with augmentation)	Accuracy(on validation set)	63.7	—	Unverified
5	LResNet50E-IR (1 model)	Accuracy(on validation set)	61.1	—	Unverified
6	Multi-task EfficientNet-B0	Accuracy(on validation set)	59.27	—	Unverified
7	resnet18_noisy	Accuracy(on validation set)	55.17	—	Unverified
8	resnet18	Accuracy(on validation set)	51.18	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PAtt-Lite	Accuracy (7 emotion)	100	—	Unverified
2	EmoNeXt	Accuracy (8 emotion)	100	—	Unverified
3	ViT + SE	Accuracy (7 emotion)	99.8	—	Unverified
4	FAN	Accuracy (7 emotion)	99.7	—	Unverified
5	Nonlinear eval on SL + SSL puzzling (B0)	Accuracy (7 emotion)	98.23	—	Unverified
6	DeepEmotion	Accuracy (7 emotion)	98	—	Unverified
7	FN2EN	Accuracy (8 emotion)	96.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	KTN	Accuracy(pretrained)	90.49	—	Unverified
2	RAN (VGG-16)	Accuracy(pretrained)	89.16	—	Unverified
3	SENet Teacher	Accuracy(pretrained)	88.88	—	Unverified
4	Local Learning Deep + BOW	Accuracy(pretrained)	87.76	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TL	Accuracy	99.52	—	Unverified
2	GReFEL	Accuracy	96.67	—	Unverified
3	ViT	Accuracy	94.83	—	Unverified
4	DeepEmotion	Accuracy	92.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Ada-DF	Accuracy	60.46	—	Unverified
2	RAN (VGG16+ResNet18)	Accuracy	56.4	—	Unverified
3	ViT + SE	Accuracy	54.29	—	Unverified
4	Island Loss	Accuracy	52.52	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GReFEL	Accuracy	72.48	—	Unverified
2	EmoAffectNet LSTM	UAR	52.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Norface	ICC	0.74	—	Unverified
2	Ours (VGG-F)	ICC	0.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Norface	ICC	0.67	—	Unverified
2	Ours (VGG-F)	ICC	0.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeepEmotion	Accuracy	99.3	—	Unverified
2	GReFEL	Accuracy	98.18	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeXpression	Accuracy	98.63	—	Unverified
2	Facial Motion Prior Network	Accuracy	82.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Dynamic MTL	Accuracy (10-fold)	89.6	—	Unverified
2	PPDN	Accuracy (10-fold)	84.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Covariance Pooling	Accuracy	87	—	Unverified
2	Multi Label Output	Accuracy	79.26	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Covariance Pooling	Accuracy	58.14	—	Unverified
2	VGG-VD-16	Accuracy	54.82	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EfficientFace	Accuracy	85.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Sequential forward selection	Accuracy	88.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EmoAffectNet LSTM	UAR	79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResEmoteNet	Accuracy	75.67	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ViT + SE	Accuracy	87.22	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EmoAffectNet LSTM	UAR	69.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EmoAffectNet LSTM	UAR	82.8	—	Unverified