167 citations · 207 across the 8 of their papers we have counts for
8 papers
CyIN: Cyclic Informative Latent Space for Bridging Complete and Incomplete Multimodal Learning
Ronghao Lin, Qiaolin He, Sijie Mai +5
Multimodal machine learning, mimicking the human brain's ability to integrate various modalities has seen rapid growth. Most previous multimodal models are trained on perfectly pai…
Multi-source Multimodal Progressive Domain Adaption for Audio-Visual Deception Detection
Ronghao Lin, Sijie Mai, Ying Zeng +3
This paper presents the winning approach for the 1st MultiModal Deception Detection (MMDD) Challenge at the 1st Workshop on Subtle Visual Computing (SVC). Aiming at the domain shif…
Meta-Learn Unimodal Signals with Weak Supervision for Multimodal Sentiment Analysis
Sijie Mai, Yu Zhao, Ying Zeng +2
Multimodal sentiment analysis aims to effectively integrate information from various sources to infer sentiment, where in many cases there are no annotations for unimodal labels. T…
End-to-end Semantic-centric Video-based Multimodal Affective Computing
Ronghao Lin, Ying Zeng, Sijie Mai +1
In the pathway toward Artificial General Intelligence (AGI), understanding human's affection is essential to enhance machine's cognition abilities. For achieving more sensual human…
Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal Representations
Sijie Mai, Ying Zeng, Haifeng Hu
Learning effective joint embedding for cross-modal data has always been a focus in the field of multimodal machine learning. We argue that during multimodal fusion, the generated m…
Which is Making the Contribution: Modulating Unimodal and Cross-modal Dynamics for Multimodal Sentiment Analysis
Ying Zeng, Sijie Mai, Haifeng Hu
Multimodal sentiment analysis (MSA) draws increasing attention with the availability of multimodal data. The boost in performance of MSA models is mainly hindered by two problems.…
Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis
Sijie Mai, Ying Zeng, Shuangjia Zheng +1
The wide application of smart devices enables the availability of multimodal data, which can be utilized in many tasks. In the field of multimodal sentiment analysis (MSA), most pr…
Analyzing Unaligned Multimodal Sequence via Graph Convolution and Graph Pooling Fusion
Sijie Mai, Songlong Xing, Jiaxuan He +2
In this paper, we study the task of multimodal sequence analysis which aims to draw inferences from visual, language and acoustic sequences. A majority of existing works generally…