Multimodal Topic Modeling
Multimodal Topic Modeling is a computational framework within topic modeling that integrates and analyzes multiple modalities of data—such as text, image, audio, or video—to jointly discover latent thematic structures that are coherent across different forms of representation.
120
Publications
5.4K
Citations
422
Authors
202
Institutions
Publications per year
2017–2026
69
Parents
120
Zhiyong Cheng, Xiaojun Chang, Lei Zhu et al. · ACM Transactions on Information Systems · 2019 · 235 citations · Full text
Learning cross-modality similarity for multinomial data
Yangqing Jia, Mathieu Salzmann, Trevor Darrell · 2011 · 197 citations
Tracking in unstructured crowded scenes
Mikel Rodríguez, Saad Ali, Takeo Kanade · 2009 · 192 citations · Full text
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202

Chinese Academy of Sciences
Beijing, China
11 h-index
28 publications
1.8K citations
Tsinghua University
Beijing, China
6 h-index
13 publications
711 citations
Institute of Automation
Beijing, China
6 h-index
12 publications
929 citations
University of Chinese Academy of Sciences
Beijing, China
6 h-index
13 publications
569 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
10 publications
889 citations
Columbia University
New York, United States
4 h-index
14 publications
630 citations

Renmin University of China
Beijing, China
4 h-index
10 publications
426 citations

University of Rochester
Rochester, United States
3 h-index
11 publications
1.2K citations
1–8 of 202
8 publications · 525 citations
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5 publications · 113 citations
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4 publications · 121 citations
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Repository · 4 publications · 87 citations
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TOMCCAP · 3 publications · 128 citations
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