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 451492 of 492 papers

TitleStatusHype
Facial Emotion Recognition: A multi-task approach using deep learningCode0
Covariance Pooling For Facial Expression RecognitionCode0
Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and ModelsCode0
Expression-aware video inpainting for HMD removal in XR applicationsCode0
Mid-level Representation Enhancement and Graph Embedded Uncertainty Suppressing for Facial Expression RecognitionCode0
Convolutional Neural Networks for Facial Expression RecognitionCode0
A Multi-resolution Approach to Expression Recognition in the WildCode0
Convolutional Neural Network Hyperparameters optimization for Facial Emotion RecognitionCode0
Island Loss for Learning Discriminative Features in Facial Expression RecognitionCode0
Prior-based Objective Inference Mining Potential Uncertainty for Facial Expression RecognitionCode0
A Compact Embedding for Facial Expression SimilarityCode0
More comprehensive facial inversion for more effective expression recognitionCode0
Joint Training on Multiple Datasets With Inconsistent Labeling Criteria for Facial Expression RecognitionCode0
Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the WildCode0
Clip-aware expressive feature learning for video-based facial expression recognitionCode0
Causal affect prediction model using a facial image sequenceCode0
Bridging the Gaps: Utilizing Unlabeled Face Recognition Datasets to Boost Semi-Supervised Facial Expression RecognitionCode0
Biased Heritage: How Datasets Shape Models in Facial Expression RecognitionCode0
AU-Supervised Convolutional Vision Transformers for Synthetic Facial Expression RecognitionCode0
Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural NetworksCode0
Exploring the Boundaries of Semi-Supervised Facial Expression Recognition using In-Distribution, Out-of-Distribution, and Unconstrained DataCode0
A Lightweight Model Enhancing Facial Expression Recognition with Spatial Bias and Cosine-Harmony LossCode0
Uncertainty-Aware Label Refinement on Hypergraphs for Personalized Federated Facial Expression RecognitionCode0
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial NetworkCode0
Subject-Based Domain Adaptation for Facial Expression RecognitionCode0
LEAF: Unveiling Two Sides of the Same Coin in Semi-supervised Facial Expression RecognitionCode0
Automatic Recognition of Student Engagement using Deep Learning and Facial ExpressionCode0
EmotionNet Nano: An Efficient Deep Convolutional Neural Network Design for Real-time Facial Expression RecognitionCode0
Learning Diversified Feature Representations for Facial Expression Recognition in the WildCode0
Active Learning with Contrastive Pre-training for Facial Expression RecognitionCode0
Assessing Demographic Bias Transfer from Dataset to Model: A Case Study in Facial Expression RecognitionCode0
eMotion-GAN: A Motion-based GAN for Photorealistic and Facial Expression Preserving Frontal View SynthesisCode0
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label DistributionCode0
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the WildCode0
Navigating Label Ambiguity for Facial Expression Recognition in the WildCode0
Learning to Amend Facial Expression Representation via De-albino and AffinityCode0
Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression RecognitionCode0
Web-based visualisation of head pose and facial expressions changes: monitoring human activity using depth dataCode0
EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction TuningCode0
EmojiHeroVR: A Study on Facial Expression Recognition under Partial Occlusion from Head-Mounted DisplaysCode0
Learn to synthesize and synthesize to learnCode0
Disentangled Source-Free Personalization for Facial Expression Recognition with Neutral Target DataCode0
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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