5 papers
Textualized and Feature-based Models for Compound Multimodal Emotion Recognition in the Wild
Nicolas Richet, Soufiane Belharbi, Haseeb Aslam +8
Systems for multimodal emotion recognition (ER) are commonly trained to extract features from different modalities (e.g., visual, audio, and textual) that are combined to predict i…
A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition
R. Gnana Praveen, Wheidima Carneiro de Melo, Nasib Ullah +8
Multimodal emotion recognition has recently gained much attention since it can leverage diverse and complementary relationships over multiple modalities (e.g., audio, visual, biosi…
Distilling Privileged Multimodal Information for Expression Recognition using Optimal Transport
Muhammad Haseeb Aslam, Muhammad Osama Zeeshan, Soufiane Belharbi +4
Deep learning models for multimodal expression recognition have reached remarkable performance in controlled laboratory environments because of their ability to learn complementary…
Subject-Based Domain Adaptation for Facial Expression Recognition
Muhammad Osama Zeeshan, Muhammad Haseeb Aslam, Soufiane Belharbi +4
Adapting a deep learning model to a specific target individual is a challenging facial expression recognition (FER) task that may be achieved using unsupervised domain adaptation (…
Joint Multimodal Transformer for Emotion Recognition in the Wild
Paul Waligora, Haseeb Aslam, Osama Zeeshan +5
Multimodal emotion recognition (MMER) systems typically outperform unimodal systems by leveraging the inter- and intra-modal relationships between, e.g., visual, textual, physiolog…