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 1081–1090 of 2041 papers

Title	Date	Tasks	Status	Hype
Semi-FedSER: Semi-supervised Learning for Speech Emotion Recognition On Federated Learning using Multiview Pseudo-Labeling	Mar 15, 2022	Emotion RecognitionFederated Learning	CodeCode Available	1
Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition	Mar 14, 2022	Arousal EstimationDominance Estimation	—Unverified	0
Audiovisual Affect Assessment and Autonomous Automobiles: Applications	Mar 14, 2022	Autonomous VehiclesEmotion Recognition	—Unverified	0
Dawn of the transformer era in speech emotion recognition: closing the valence gap	Mar 14, 2022	Cross-corpusEmotion Recognition	CodeCode Available	2
EventFormer: AU Event Transformer for Facial Action Unit Event Detection	Mar 12, 2022	Emotion RecognitionEvent Detection	—Unverified	0
Robust Federated Learning Against Adversarial Attacks for Speech Emotion Recognition	Mar 9, 2022	Emotion RecognitionFederated Learning	—Unverified	0
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors	Mar 8, 2022	AttributeEmotion Classification	—Unverified	0
Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributes	Mar 5, 2022	AttributeEmotion Recognition	CodeCode Available	0
MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in Conversations	Mar 4, 2022	Emotion RecognitionEmotion Recognition in Conversation	CodeCode Available	1
Attention-based Region of Interest (ROI) Detection for Speech Emotion Recognition	Mar 3, 2022	Emotion RecognitionMulti-class Classification	—Unverified	0

Show:10 25 50

← PrevPage 109 of 205Next →

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