Emotion Recognition

Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 961–970 of 2041 papers

Title	Date	Tasks	Status	Hype
Label Uncertainty Modeling and Prediction for Speech Emotion Recognition using t-Distributions	Jul 25, 2022	Emotion RecognitionSpeech Emotion Recognition	CodeCode Available	0
Seeking Subjectivity in Visual Emotion Distribution Learning	Jul 25, 2022	Emotion Recognition	—Unverified	0
Affective Behaviour Analysis Using Pretrained Model with Facial Priori	Jul 24, 2022	Emotion Recognition	CodeCode Available	1
Multimodal Emotion Recognition with Modality-Pairwise Unsupervised Contrastive Loss	Jul 23, 2022	Cultural Vocal Bursts Intensity PredictionEmotion Recognition	CodeCode Available	1
Affective Behavior Analysis using Action Unit Relation Graph and Multi-task Cross Attention	Jul 21, 2022	Action Unit DetectionArousal Estimation	—Unverified	0
BYEL : Bootstrap Your Emotion Latent	Jul 20, 2022	Emotion ClassificationEmotion Recognition	CodeCode Available	0
HSE-NN Team at the 4th ABAW Competition: Multi-task Emotion Recognition and Learning from Synthetic Images	Jul 19, 2022	Emotion RecognitionMulti-Task Learning	—Unverified	0
Multi-Task Learning Framework for Emotion Recognition in-the-wild	Jul 19, 2022	Emotion RecognitionMulti-Task Learning	CodeCode Available	0
CTL-MTNet: A Novel CapsNet and Transfer Learning-Based Mixed Task Net for the Single-Corpus and Cross-Corpus Speech Emotion Recognition	Jul 18, 2022	Cross-corpusEmotion Recognition	CodeCode Available	0
A Multibias-mitigated and Sentiment Knowledge Enriched Transformer for Debiasing in Multimodal Conversational Emotion Recognition	Jul 17, 2022	Emotion RecognitionMultimodal Emotion Recognition	—Unverified	0

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All datasets Emomusic RAVDESS EMOTIC FER2013 MaSaC_ERC MPED MSP-Podcast SEED คลิปคุณพ่อให้ลูกสาวยืมโทรศัพท์และความสนุกสนาน

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	M2D-CLAP	EmoA	77.4	—	Unverified
2	M2D2	EmoA	76.7	—	Unverified
3	M2D	EmoA	76.1	—	Unverified
4	Jukebox (Pre-training: CALM)	EmoA	72.1	—	Unverified
5	CLMR (Pre-training: contrastive)	EmoA	67.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LogisticRegression on posteriors of xlsr-Wav2Vec2.0&bi-LSTM+Attention	Accuracy	86.7	—	Unverified
2	MultiMAE-DER	WAR	83.61	—	Unverified
3	Intermediate-Attention-Fusion	Accuracy	81.58	—	Unverified
4	Logistic Regression on posteriors of the CNN-14&biLSTM-GuidedST	Accuracy	80.08	—	Unverified
5	ERANN-0-4	Accuracy	74.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CAGE	Top-3 Accuracy (%)	14.73	—	Unverified
2	FocusCLIP	Top-3 Accuracy (%)	13.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VGG based	5-class test accuracy	66.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MaSaC-ERC-Z	F1-score (Weighted)	51.17	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BiHDM	Accuracy	40.34	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	w2v2-L-robust-12	Concordance correlation coefficient (CCC)	0.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	4D-aNN	Accuracy	96.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	1'"	1	—	Unverified