5 citations · 22 across the 8 of their papers we have counts for
8 papers
A Survey of Stance Detection on Social Media: New Directions and Perspectives
Bowen Zhang, Genan Dai, Fuqiang Niu +5
In modern digital environments, users frequently express opinions on contentious topics, providing a wealth of information on prevailing attitudes. The systematic analysis of these…
Revisiting Multimodal Emotion Recognition in Conversation from the Perspective of Graph Spectrum
Tao Meng, Fuchen Zhang, Yuntao Shou +3
Efficiently capturing consistent and complementary semantic features in a multimodal conversation context is crucial for Multimodal Emotion Recognition in Conversation (MERC). Exis…
Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusion
Yuntao Shou, Tao Meng, Fuchen Zhang +2
Multi-modal Emotion Recognition in Conversation (MERC) has received considerable attention in various fields, e.g., human-computer interaction and recommendation systems. Most exis…
Deep Imbalanced Learning for Multimodal Emotion Recognition in Conversations
Tao Meng, Yuntao Shou, Wei Ai +2
The main task of Multimodal Emotion Recognition in Conversations (MERC) is to identify the emotions in modalities, e.g., text, audio, image and video, which is a significant develo…
Adversarial Representation with Intra-Modal and Inter-Modal Graph Contrastive Learning for Multimodal Emotion Recognition
Yuntao Shou, Tao Meng, Wei Ai +2
With the release of increasing open-source emotion recognition datasets on social media platforms and the rapid development of computing resources, multimodal emotion recognition t…
DER-GCN: Dialogue and Event Relation-Aware Graph Convolutional Neural Network for Multimodal Dialogue Emotion Recognition
Wei Ai, Yuntao Shou, Tao Meng +2
With the continuous development of deep learning (DL), the task of multimodal dialogue emotion recognition (MDER) has recently received extensive research attention, which is also…
A Comprehensive Survey on Multi-modal Conversational Emotion Recognition with Deep Learning
Yuntao Shou, Tao Meng, Wei Ai +3
Multi-modal conversation emotion recognition (MCER) aims to recognize and track the speaker's emotional state using text, speech, and visual information in the conversation scene.…
CILF-CIAE: CLIP-driven Image-Language Fusion for Correcting Inverse Age Estimation
Yuntao Shou, Wei Ai, Tao Meng +2
The age estimation task aims to predict the age of an individual by analyzing facial features in an image. The development of age estimation can improve the efficiency and accuracy…