A low-rank matching attention based cross-modal feature fusion method for conversational emotion recognition
Conversational emotion recognition (CER) is an important research topic in human-
computer interactions. Although recent advancements in transformer-based cross-modal …
computer interactions. Although recent advancements in transformer-based cross-modal …
Efficient multimodal transformer with dual-level feature restoration for robust multimodal sentiment analysis
With the proliferation of user-generated online videos, Multimodal Sentiment Analysis (MSA)
has attracted increasing attention recently. Despite significant progress, there are still two …
has attracted increasing attention recently. Despite significant progress, there are still two …
Smin: Semi-supervised multi-modal interaction network for conversational emotion recognition
Conversational emotion recognition is a crucial research topic in human-computer
interactions. Due to the heavy annotation cost and inevitable label ambiguity, collecting …
interactions. Due to the heavy annotation cost and inevitable label ambiguity, collecting …
SKEAFN: sentiment knowledge enhanced attention fusion network for multimodal sentiment analysis
Multimodal sentiment analysis is an active research field that aims to recognize the user's
sentiment information from multimodal data. The primary challenge in this field is to develop …
sentiment information from multimodal data. The primary challenge in this field is to develop …
Fc-kan: Function combinations in kolmogorov-arnold networks
In this paper, we introduce FC-KAN, a Kolmogorov-Arnold Network (KAN) that leverages
combinations of popular mathematical functions such as B-splines, wavelets, and radial …
combinations of popular mathematical functions such as B-splines, wavelets, and radial …
Attention gated tensor neural network architectures for speech emotion recognition
In an attempt to make Human-Computer Interactions more natural, we propose the use of
Tensor Factorized Neural Networks (TFNN) and Attention Gated Tensor Factorized Neural …
Tensor Factorized Neural Networks (TFNN) and Attention Gated Tensor Factorized Neural …
Multi-granularity relational attention network for audio-visual question answering
Recent methods for video question answering (VideoQA), aiming to generate answers
based on given questions and video content, have made significant progress in cross-modal …
based on given questions and video content, have made significant progress in cross-modal …
Low-rank Prompt Interaction for Continual Vision-Language Retrieval
Research on continual learning in multi-modal tasks has been receiving increasing
attention. However, most existing work overlooks the explicit cross-modal and cross-task …
attention. However, most existing work overlooks the explicit cross-modal and cross-task …
Pirnet: Personality-enhanced iterative refinement network for emotion recognition in conversation
Emotion recognition in conversation (ERC) is important for enhancing user experience in
human–computer interaction. Unlike vanilla emotion recognition in individual utterances …
human–computer interaction. Unlike vanilla emotion recognition in individual utterances …
Real-time multimodal interaction in virtual reality-a case study with a large virtual interface
The values of VR and multimodal interaction technologies offer creative, virtual alternatives
to manipulate a large data set in a virtual environment. This work presents the design …
to manipulate a large data set in a virtual environment. This work presents the design …