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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

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Showing 676–700 of 2041 papers

TitleStatusHype
EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition—0
EmoNets: Multimodal deep learning approaches for emotion recognition in video—0
EEG-SCMM: Soft Contrastive Masked Modeling for Cross-Corpus EEG-Based Emotion Recognition—0
EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions—0
EmoSens: Emotion Recognition based on Sensor data analysis using LightGBM—0
EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters—0
EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification—0
Biologically inspired speech emotion recognition—0
Adversarial Representation with Intra-Modal and Inter-Modal Graph Contrastive Learning for Multimodal Emotion Recognition—0
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network—0
EmotiCon: Context-Aware Multimodal Emotion Recognition using Frege's Principle—0
EmotiCrafter: Text-to-Emotional-Image Generation based on Valence-Arousal Model—0
EmotiEffNet Facial Features in Uni-task Emotion Recognition in Video at ABAW-5 competition—0
EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG with An Application to Emotion Recognition—0
CAST-Phys: Contactless Affective States Through Physiological signals Database—0
Emotional Images: Assessing Emotions in Images and Potential Biases in Generative Models—0
Emotional Intelligence of Large Language Models—0
Emotionally-Informed Models for Detecting Moments of Change and Suicide Risk Levels in Longitudinal Social Media Data—0
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation—0
EEG emotion recognition using dynamical graph convolutional neural networks—0
Bimodal Speech Emotion Recognition Using Pre-Trained Language Models—0
Emotional Voice Messages (EMOVOME) database: emotion recognition in spontaneous voice messages—0
Emotion analysis and detection during COVID-19—0
Annotated Corpus of Tweets in English from Various Domains for Emotion Detection—0
Bimodal Connection Attention Fusion for Speech Emotion Recognition—0
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All datasetsEmomusicRAVDESSEMOTICFER2013MaSaC_ERCMPEDMSP-PodcastSEEDคลิปคุณพ่อให้ลูกสาวยืมโทรศัพท์และความสนุกสนาน

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1M2D-CLAPEmoA77.4—Unverified
2M2D2EmoA76.7—Unverified
3M2DEmoA76.1—Unverified
4Jukebox (Pre-training: CALM)EmoA72.1—Unverified
5CLMR (Pre-training: contrastive)EmoA67.8—Unverified
#ModelMetricClaimedVerifiedStatus
1LogisticRegression on posteriors of xlsr-Wav2Vec2.0&bi-LSTM+AttentionAccuracy86.7—Unverified
2MultiMAE-DERWAR83.61—Unverified
3Intermediate-Attention-FusionAccuracy81.58—Unverified
4Logistic Regression on posteriors of the CNN-14&biLSTM-GuidedSTAccuracy80.08—Unverified
5ERANN-0-4Accuracy74.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CAGETop-3 Accuracy (%)14.73—Unverified
2FocusCLIPTop-3 Accuracy (%)13.73—Unverified
#ModelMetricClaimedVerifiedStatus
1VGG based5-class test accuracy66.13—Unverified
#ModelMetricClaimedVerifiedStatus
1MaSaC-ERC-ZF1-score (Weighted)51.17—Unverified
#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy40.34—Unverified
#ModelMetricClaimedVerifiedStatus
1w2v2-L-robust-12Concordance correlation coefficient (CCC)0.64—Unverified
#ModelMetricClaimedVerifiedStatus
14D-aNNAccuracy96.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN1'"1—Unverified