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 151–175 of 492 papers

Title	Date	Tasks	Status
Facial Expression Recognition Based on Complexity Perception Classification Algorithm	Mar 1, 2018	ClassificationFacial Expression Recognition	—Unverified
Facial expression recognition based on local region specific features and support vector machines	Apr 15, 2016	Emotion RecognitionFacial Expression Recognition	—Unverified
Facial Expression Recognition by De-Expression Residue Learning	Jun 1, 2018	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Class adaptive threshold and negative class guided noisy annotation robust Facial Expression Recognition	May 3, 2023	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Evaluation of the Spatio-Temporal features and GAN for Micro-expression Recognition System	Apr 3, 2019	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
CIAO! A Contrastive Adaptation Mechanism for Non-Universal Facial Expression Recognition	Aug 10, 2022	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Evaluating Facial Expression Recognition Datasets for Deep Learning: A Benchmark Study with Novel Similarity Metrics	Mar 26, 2025	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Emotion Recognition in Speech using Cross-Modal Transfer in the Wild	Aug 16, 2018	Emotion RecognitionFacial Emotion Recognition	—Unverified
A novel database of Children's Spontaneous Facial Expressions (LIRIS-CSE)	Dec 4, 2018	BenchmarkingFacial Expression Recognition	—Unverified
Advanced local motion patterns for macro and micro facial expression recognition	May 4, 2018	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Facial Expression Recognition at the Edge: CPU vs GPU vs VPU vs TPU	May 17, 2023	CPUFacial Expression Recognition	—Unverified
Facial Expression Recognition from World Wild Web	May 11, 2016	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Face Trees for Expression Recognition	Dec 5, 2021	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
EXPERTNet Exigent Features Preservative Network for Facial Expression Recognition	Apr 14, 2019	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
CASIA-Face-Africa: A Large-scale African Face Image Database	May 8, 2021	Age EstimationFace Recognition	—Unverified
Emotic Masked Autoencoder with Attention Fusion for Facial Expression Recognition	Mar 19, 2024	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Capturing Complex Spatio-temporal Relations among Facial Muscles for Facial Expression Recognition	Jun 1, 2013	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
Facial Emotion Recognition using Convolutional Neural Networks	Oct 12, 2019	Emotion RecognitionFacial Emotion Recognition	—Unverified
Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition	Dec 27, 2020	Emotion RecognitionFacial Expression Recognition (FER)	—Unverified
Exploring Facial Expression Recognition through Semi-Supervised Pretraining and Temporal Modeling	Mar 18, 2024	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified
CAKE: Compact and Accurate K-dimensional representation of Emotion	Jul 30, 2018	Emotion RecognitionFacial Expression Recognition (FER)	—Unverified
Exploring Large-scale Unlabeled Faces to Enhance Facial Expression Recognition	Mar 15, 2023	Emotion RecognitionFace Recognition	—Unverified
An optimized Capsule-LSTM model for facial expression recognition with video sequences	May 27, 2021	DecoderFacial Expression Recognition	—Unverified
Expression Analysis Based on Face Regions in Read-world Conditions	Oct 23, 2019	Emotion RecognitionFacial Emotion Recognition	—Unverified
E-FCNN for tiny facial expression recognition	Aug 20, 2020	Facial Expression RecognitionFacial Expression Recognition (FER)	—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	EmoNeXt	Accuracy (8 emotion)	100	—	Unverified
2	PAtt-Lite	Accuracy (7 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