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

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Showing 91–100 of 458 papers

Title	Date	Tasks	Status
Converting Sentiment Annotated Data to Emotion Annotated Data	Dec 1, 2019	Emotion ClassificationEmotion Recognition	—Unverified
Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video	Nov 13, 2017	Emotion ClassificationEmotion Recognition	—Unverified
Corpus Fusion for Emotion Classification	Dec 1, 2016	BIG-bench Machine LearningClassification	—Unverified
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features	Nov 16, 2021	Cultural Vocal Bursts Intensity PredictionEmotion Classification	—Unverified
Adaptive Transfer Learning for Multi-Label Emotion Classification	Jan 16, 2022	ClassificationEmotion Classification	—Unverified
A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation	Jan 30, 2022	Emotion ClassificationEmotion Recognition	—Unverified
Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition	Jan 25, 2025	cross-modal alignmentEmotion Classification	—Unverified
Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition	Dec 2, 2024	Active LearningCross-corpus	—Unverified
Crowdsourcing and Validating Event-focused Emotion Corpora for German and English	May 31, 2019	Emotion ClassificationEmotion Recognition	—Unverified
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation	Apr 17, 2024	Emotion ClassificationEmotion Recognition	—Unverified

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All datasets CMU-MOSEI SemEval 2018 Task 1E-c EWALK MFA ROCStories ArmanEmo CAER-Dynamic RAVDESS ShortPersianEmo

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MARLIN (ViT-L)	Accuracy	80.63	—	Unverified
2	MARLIN (ViT-B)	Accuracy	80.6	—	Unverified
3	MARLIN (ViT-S)	Accuracy	80.38	—	Unverified
4	ConCluGen	Accuracy	66.48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SpanEmo	Accuracy	0.6	—	Unverified
2	BERT+DK	Accuracy	0.59	—	Unverified
3	BERT-GCN	Accuracy	0.59	—	Unverified
4	Transformer (finetune)	Macro-F1	0.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ProxEmo (ours)	Accuracy	82.4	—	Unverified
2	STEP [bhattacharya2019step]	Accuracy	78.24	—	Unverified
3	Baseline (Vanilla LSTM) [Ewalk]	Accuracy	55.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MLKNN	F-F1 score (Comb.)	0.34	—	Unverified
2	CC - XGB	F-F1 score (Comb.)	0.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Semi-supervision	F1	65.88	—	Unverified
2	NPN + Explanation Training	F1	30.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Deep ParsBERT	Macro F1	0.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CAERNet	Accuracy	77.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ERANN-0-4	Top-1 Accuracy	74.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Deep ParsBERT	Macro F1	0.71	—	Unverified