SOTAVerified

Emotion Classification

Emotion classification, or emotion categorization, is the task of recognising emotions to classify them into the corresponding category. Given an input, classify it as 'neutral or no emotion' or as one, or more, of several given emotions that best represent the mental state of the subject's facial expression, words, and so on. Some example benchmarks include ROCStories, Many Faces of Anger (MFA), and GoEmotions. Models can be evaluated using metrics such as the Concordance Correlation Coefficient (CCC) and the Mean Squared Error (MSE).

Papers

Showing 150 of 458 papers

TitleStatusHype
EmT: A Novel Transformer for Generalized Cross-subject EEG Emotion RecognitionCode2
MARLIN: Masked Autoencoder for facial video Representation LearnINgCode2
Emotion Classification in a Resource Constrained Language Using Transformer-based ApproachCode1
SpanEmo: Casting Multi-label Emotion Classification as Span-predictionCode1
Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task ApproachCode1
EmoNeXt: an Adapted ConvNeXt for Facial Emotion RecognitionCode1
Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across CorporaCode1
Label-Aware Hyperbolic Embeddings for Fine-grained Emotion ClassificationCode1
PARSE: Pairwise Alignment of Representations in Semi-Supervised EEG Learning for Emotion RecognitionCode1
SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment SemanticsCode1
StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time SeriesCode1
EMelodyGen: Emotion-Conditioned Melody Generation in ABC Notation with the Musical Feature TemplateCode1
Evaluating Emotion Arcs Across Languages: Bridging the Global Divide in Sentiment AnalysisCode1
PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English PoetryCode1
Accurate Emotion Strength Assessment for Seen and Unseen Speech Based on Data-Driven Deep LearningCode1
GoEmotions: A Dataset of Fine-Grained EmotionsCode1
BERT-like Pre-training for Symbolic Piano Music Classification TasksCode1
Multi-Task Multi-Modal Self-Supervised Learning for Facial Expression RecognitionCode1
Efficient Speech Emotion Recognition Using Multi-Scale CNN and AttentionCode1
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text ClassificationCode1
Perception for Autonomous Systems (PAZ)Code1
Real-Time Emotion Classification Using EEG Data Stream in E-Learning ContextsCode1
EmoVIT: Revolutionizing Emotion Insights with Visual Instruction TuningCode1
Twitter Sentiment AnalysisCode1
VANPY: Voice Analysis FrameworkCode1
VLLMs Provide Better Context for Emotion Understanding Through Common Sense ReasoningCode1
Learning Arousal-Valence Representation from Categorical Emotion Labels of SpeechCode1
GiMeFive: Towards Interpretable Facial Emotion ClassificationCode1
ProxEmo: Gait-based Emotion Learning and Multi-view Proxemic Fusion for Socially-Aware Robot NavigationCode1
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical NetworksCode1
Nkululeko: A Tool For Rapid Speaker Characteristics DetectionCode1
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion RecognitionCode1
Is Cross-Attention Preferable to Self-Attention for Multi-Modal Emotion Recognition?Code1
Speech Emotion Recognition with Multi-Task LearningCode1
MELLM: Exploring LLM-Powered Micro-Expression Understanding Enhanced by Subtle Motion PerceptionCode1
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language RepresentationsCode1
Modeling Label Semantics for Predicting Emotional ReactionsCode1
A novel Fourier Adjacency Transformer for advanced EEG emotion recognitionCode1
DialogueRNN: An Attentive RNN for Emotion Detection in ConversationsCode1
Domain-Invariant Representation Learning from EEG with Private EncodersCode1
None Class Ranking Loss for Document-Level Relation ExtractionCode1
FerNeXt: Facial Expression Recognition Using ConvNeXt with Channel AttentionCode0
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph Convolution NetworksCode0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networksCode0
Facial Affect Recognition in the Wild Using Multi-Task Learning Convolutional NetworkCode0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networksCode0
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural AnnotatorsCode0
Enhancing Cognitive Models of Emotions with Representation LearningCode0
Exploiting Multiple EEG Data Domains with Adversarial LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MARLIN (ViT-L)Accuracy80.63Unverified
2MARLIN (ViT-B)Accuracy80.6Unverified
3MARLIN (ViT-S)Accuracy80.38Unverified
4ConCluGenAccuracy66.48Unverified
#ModelMetricClaimedVerifiedStatus
1SpanEmoAccuracy0.6Unverified
2BERT+DKAccuracy0.59Unverified
3BERT-GCNAccuracy0.59Unverified
4Transformer (finetune)Macro-F10.56Unverified
#ModelMetricClaimedVerifiedStatus
1ProxEmo (ours)Accuracy82.4Unverified
2STEP [bhattacharya2019step]Accuracy78.24Unverified
3Baseline (Vanilla LSTM) [Ewalk]Accuracy55.47Unverified
#ModelMetricClaimedVerifiedStatus
1MLKNNF-F1 score (Comb.)0.34Unverified
2CC - XGBF-F1 score (Comb.)0.33Unverified
#ModelMetricClaimedVerifiedStatus
1Semi-supervisionF165.88Unverified
2NPN + Explanation TrainingF130.29Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.65Unverified
#ModelMetricClaimedVerifiedStatus
1CAERNetAccuracy77.04Unverified
#ModelMetricClaimedVerifiedStatus
1ERANN-0-4Top-1 Accuracy74.8Unverified
#ModelMetricClaimedVerifiedStatus
1Deep ParsBERTMacro F10.71Unverified