SOTAVerified

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

Showing 101150 of 492 papers

TitleStatusHype
ASM: Adaptive Sample Mining for In-The-Wild Facial Expression RecognitionCode0
Convolutional Neural Network Hyperparameters optimization for Facial Emotion RecognitionCode0
Learning to Amend Facial Expression Representation via De-albino and AffinityCode0
Masked Student Dataset of ExpressionsCode0
Covariance Pooling For Facial Expression RecognitionCode0
Mid-level Representation Enhancement and Graph Embedded Uncertainty Suppressing for Facial Expression RecognitionCode0
Learning Diversified Feature Representations for Facial Expression Recognition in the WildCode0
ARBEx: Attentive Feature Extraction with Reliability Balancing for Robust Facial Expression LearningCode0
Joint Training on Multiple Datasets With Inconsistent Labeling Criteria for Facial Expression RecognitionCode0
Coarse-to-Fine Cascaded Networks with Smooth Predicting for Video Facial Expression RecognitionCode0
Island Loss for Learning Discriminative Features in Facial Expression RecognitionCode0
LEAF: Unveiling Two Sides of the Same Coin in Semi-supervised Facial Expression RecognitionCode0
Grammatical facial expression recognition using customized deep neural network architectureCode0
Clip-aware expressive feature learning for video-based facial expression recognitionCode0
Classifying emotions and engagement in online learning based on a single facial expression recognition neural networkCode0
4DFAB: A Large Scale 4D Facial Expression Database for Biometric ApplicationsCode0
GCF: Graph Convolutional Networks for Facial Expression RecognitionCode0
Causal affect prediction model using a facial image sequenceCode0
Greedy Search for Descriptive Spatial Face FeaturesCode0
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel AttentionCode0
FERAtt: Facial Expression Recognition with Attention NetCode0
Frame attention networks for facial expression recognition in videosCode0
Facial expression recognition with grid-wise attention and visual transformerCode0
A Multi-resolution Approach to Expression Recognition in the WildCode0
Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural NetworksCode0
Facial Motion Prior Networks for Facial Expression RecognitionCode0
Active Learning with Contrastive Pre-training for Facial Expression RecognitionCode0
Facial Expression Recognition Under Partial Occlusion from Virtual Reality Headsets based on Transfer LearningCode0
Dynamic Adaptive Threshold based Learning for Noisy Annotations Robust Facial Expression RecognitionCode0
Facial Expression Recognition Research Based on Deep LearningCode0
Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and ModelsCode0
Expression-aware video inpainting for HMD removal in XR applicationsCode0
Biased Heritage: How Datasets Shape Models in Facial Expression RecognitionCode0
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial NetworkCode0
Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression RecognitionCode0
A Compact Embedding for Facial Expression SimilarityCode0
Exploring the Boundaries of Semi-Supervised Facial Expression Recognition using In-Distribution, Out-of-Distribution, and Unconstrained DataCode0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networksCode0
eMotion-GAN: A Motion-based GAN for Photorealistic and Facial Expression Preserving Frontal View SynthesisCode0
EmotionNet Nano: An Efficient Deep Convolutional Neural Network Design for Real-time Facial Expression RecognitionCode0
EmojiHeroVR: A Study on Facial Expression Recognition under Partial Occlusion from Head-Mounted DisplaysCode0
Facial Emotion Recognition: A multi-task approach using deep learningCode0
A Lightweight Model Enhancing Facial Expression Recognition with Spatial Bias and Cosine-Harmony LossCode0
EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction TuningCode0
Automatic Recognition of Student Engagement using Deep Learning and Facial ExpressionCode0
Dynamic Multi-Task Learning for Face Recognition with Facial ExpressionCode0
Disentangled Source-Free Personalization for Facial Expression Recognition with Neutral Target DataCode0
Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the WildCode0
Bridging the Gaps: Utilizing Unlabeled Face Recognition Datasets to Boost Semi-Supervised Facial Expression RecognitionCode0
DeXpression: Deep Convolutional Neural Network for Expression RecognitionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResEmoteNetAccuracy (7 emotion)72.93Unverified
2NorfaceAccuracy (8 emotion)68.69Unverified
3EmoAffectNetAccuracy (7 emotion)66.49Unverified
4Emotion-GCNAccuracy (7 emotion)66.46Unverified
5FaceBehaviorNetAccuracy (7 emotion)65.4Unverified
6Ada-DFAccuracy (7 emotion)65.34Unverified
7EACAccuracy (7 emotion)65.32Unverified
8PAENetAccuracy (7 emotion)65.29Unverified
9DACLAccuracy (7 emotion)65.2Unverified
10DDAMFN++Accuracy (8 emotion)65.04Unverified
#ModelMetricClaimedVerifiedStatus
1ResEmoteNetOverall Accuracy94.76Unverified
2FMAEOverall Accuracy93.45Unverified
3QCSOverall Accuracy93.02Unverified
4NorfaceOverall Accuracy92.97Unverified
5S2DOverall Accuracy92.57Unverified
6BTNOverall Accuracy92.54Unverified
7GReFELOverall Accuracy92.47Unverified
8DDAMFN++Overall Accuracy92.34Unverified
9DCJTOverall Accuracy92.24Unverified
10POSTER++Overall Accuracy92.21Unverified
#ModelMetricClaimedVerifiedStatus
1EfficientFERAccuracy82.47Unverified
2FERNeXt-SDAFEAccuracy81.33Unverified
3ResEmoteNetAccuracy79.79Unverified
4Ensemble ResMaskingNet with 6 other CNNsAccuracy76.82Unverified
5Mini-ResEmoteNet (A)Accuracy76.33Unverified
6EmoNeXtAccuracy76.12Unverified
7Segmentation VGG-19Accuracy75.97Unverified
8Local Learning Deep+BOWAccuracy75.42Unverified
9LHC-NetAccuracy74.42Unverified
10Residual Masking NetworkAccuracy74.14Unverified
#ModelMetricClaimedVerifiedStatus
1PAtt-LiteAccuracy95.55Unverified
2GReFELAccuracy93.09Unverified
3QCSAccuracy91.85Unverified
4ResNet18 Dense ArchitectureAccuracy91.41Unverified
5DDAMFNAccuracy90.74Unverified
6KTNAccuracy90.49Unverified
7Vit-base + MAEAccuracy90.18Unverified
8FER-VTAccuracy90.04Unverified
9EACAccuracy89.64Unverified
10LResNet50E-IRAccuracy89.26Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50Accuracy(on validation set)65.5Unverified
2LResNet50E-IR (5 models with augmentation)Accuracy(on validation set)65.5Unverified
3EACAccuracy(on validation set)65.32Unverified
4LResNet50E-IR (1 model with augmentation)Accuracy(on validation set)63.7Unverified
5LResNet50E-IR (1 model)Accuracy(on validation set)61.1Unverified
6Multi-task EfficientNet-B0Accuracy(on validation set)59.27Unverified
7resnet18_noisyAccuracy(on validation set)55.17Unverified
8resnet18Accuracy(on validation set)51.18Unverified
#ModelMetricClaimedVerifiedStatus
1EmoNeXtAccuracy (8 emotion)100Unverified
2PAtt-LiteAccuracy (7 emotion)100Unverified
3ViT + SEAccuracy (7 emotion)99.8Unverified
4FANAccuracy (7 emotion)99.7Unverified
5Nonlinear eval on SL + SSL puzzling (B0)Accuracy (7 emotion)98.23Unverified
6DeepEmotionAccuracy (7 emotion)98Unverified
7FN2ENAccuracy (8 emotion)96.8Unverified
#ModelMetricClaimedVerifiedStatus
1KTNAccuracy(pretrained)90.49Unverified
2RAN (VGG-16)Accuracy(pretrained)89.16Unverified
3SENet TeacherAccuracy(pretrained)88.88Unverified
4Local Learning Deep + BOWAccuracy(pretrained)87.76Unverified
#ModelMetricClaimedVerifiedStatus
1TLAccuracy99.52Unverified
2GReFELAccuracy96.67Unverified
3ViTAccuracy94.83Unverified
4DeepEmotionAccuracy92.8Unverified
#ModelMetricClaimedVerifiedStatus
1Ada-DFAccuracy60.46Unverified
2RAN (VGG16+ResNet18)Accuracy56.4Unverified
3ViT + SEAccuracy54.29Unverified
4Island LossAccuracy52.52Unverified
#ModelMetricClaimedVerifiedStatus
1GReFELAccuracy72.48Unverified
2EmoAffectNet LSTMUAR52.9Unverified
#ModelMetricClaimedVerifiedStatus
1NorfaceICC0.74Unverified
2Ours (VGG-F)ICC0.72Unverified
#ModelMetricClaimedVerifiedStatus
1NorfaceICC0.67Unverified
2Ours (VGG-F)ICC0.6Unverified
#ModelMetricClaimedVerifiedStatus
1DeepEmotionAccuracy99.3Unverified
2GReFELAccuracy98.18Unverified
#ModelMetricClaimedVerifiedStatus
1DeXpressionAccuracy98.63Unverified
2Facial Motion Prior NetworkAccuracy82.74Unverified
#ModelMetricClaimedVerifiedStatus
1Dynamic MTLAccuracy (10-fold)89.6Unverified
2PPDNAccuracy (10-fold)84.59Unverified
#ModelMetricClaimedVerifiedStatus
1Covariance PoolingAccuracy87Unverified
2Multi Label OutputAccuracy79.26Unverified
#ModelMetricClaimedVerifiedStatus
1Covariance PoolingAccuracy58.14Unverified
2VGG-VD-16Accuracy54.82Unverified
#ModelMetricClaimedVerifiedStatus
1EfficientFaceAccuracy 85.87Unverified
#ModelMetricClaimedVerifiedStatus
1Sequential forward selectionAccuracy88.7Unverified
#ModelMetricClaimedVerifiedStatus
1EmoAffectNet LSTMUAR79Unverified
#ModelMetricClaimedVerifiedStatus
1ResEmoteNetAccuracy75.67Unverified
#ModelMetricClaimedVerifiedStatus
1ViT + SEAccuracy87.22Unverified
#ModelMetricClaimedVerifiedStatus
1EmoAffectNet LSTMUAR69.7Unverified
#ModelMetricClaimedVerifiedStatus
1EmoAffectNet LSTMUAR82.8Unverified