Heterogeneous Contrastive Learning for Foundation Models and Beyond
In the era of big data and Artificial Intelligence, an emerging paradigm is to utilize contrastive
self-supervised learning to model large-scale heterogeneous data. Many existing foundation …
self-supervised learning to model large-scale heterogeneous data. Many existing foundation …
On the consensus of synchronous temporal and spatial views: A novel multimodal deep learning method for social video prediction
The blowout development of video social platforms has spawned a wide range of social
video prediction (SVP) tasks, such as video attractiveness prediction and video sentiment …
video prediction (SVP) tasks, such as video attractiveness prediction and video sentiment …
A Multi-Level Alignment and Cross-Modal Unified Semantic Graph Refinement Network for Conversational Emotion Recognition
X Zhang, W Cui, B Hu, Y Li - IEEE Transactions on Affective …, 2024 - ieeexplore.ieee.org
Emotion recognition in conversation (ERC) based on multiple modalities has attracted
enormous attention. However, most research simply concatenated multimodal …
enormous attention. However, most research simply concatenated multimodal …
TCHFN: Multimodal sentiment analysis based on Text-Centric Hierarchical Fusion Network
Multimodal sentiment analysis (MSA) has become a popular field of research in recent
years. The aim is to combine the three modalities of text, video, and audio to obtain …
years. The aim is to combine the three modalities of text, video, and audio to obtain …
[HTML][HTML] 结合时间注意力机制和单模态标签自动生成策略的自监督多模态情感识别
孙强， 王姝玉 - 电子与信息学报, 2024 - jeit.ac.cn
大多数多模态情感识别方法旨在寻求一种有效的融合机制, 构建异构模态的特征,
从而学习到具有语义一致性的特征表示. 然而, 这些方法通常忽略了模态间情感语义的差异性 …
从而学习到具有语义一致性的特征表示. 然而, 这些方法通常忽略了模态间情感语义的差异性 …
HyDiscGAN: A Hybrid Distributed cGAN for Audio-Visual Privacy Preservation in Multimodal Sentiment Analysis
Multimodal Sentiment Analysis (MSA) aims to identify speakers' sentiment tendencies in
multimodal video content, raising serious concerns about privacy risks associated with …
multimodal video content, raising serious concerns about privacy risks associated with …
CLGSI: A Multimodal Sentiment Analysis Framework based on Contrastive Learning Guided by Sentiment Intensity
Recently, contrastive learning has begun to gain popularity in multimodal sentiment analysis
(MSA). However, most of existing MSA methods based on contrastive learning lacks more …
(MSA). However, most of existing MSA methods based on contrastive learning lacks more …
InfoEnh: Towards Multimodal Sentiment Analysis via Information Bottleneck Filter and Optimal Transport Alignment
Y Xie, Z Zhu, X Lu, Z Huang… - Proceedings of the 2024 …, 2024 - aclanthology.org
Abstract In recent years, Multimodal Sentiment Analysis (MSA) leveraging deep learning has
demonstrated exceptional performance in a wide range of domains. Its success lies in …
demonstrated exceptional performance in a wide range of domains. Its success lies in …
Self-supervised Multimodal Emotion Recognition Combining Temporal Attention Mechanism and Unimodal Label Automatic Generation Strategy
Q SUN, S WANG - 电子与信息学报, 2024 - jeit.ac.cn
Most multimodal emotion recognition methods aim to find an effective fusion mechanism to
construct the features from heterogeneous modalities, so as to learn the feature …
construct the features from heterogeneous modalities, so as to learn the feature …
Prototype-Oriented Multimodal Emotion Contrast-Enhancer
Q Yang, S Tian, L Yu, X Fan, J Song - papers.ssrn.com
Prototype learning has been proven effective and reliable for few-shot learning. Recently, a
series of outstanding models have emerged in multimodal sentiment analysis. However, the …
series of outstanding models have emerged in multimodal sentiment analysis. However, the …