Multimodal Summarization
Multimodal Summarization is a computational framework that synthesizes cohesive and concise representations from aligned inputs across multiple modalities—such as text, audio, and visual data—by identifying and integrating salient information while preserving cross-modal semantics and hierarchical structure.
145
Publications
5.4K
Citations
477
Authors
177
Institutions
Publications per year
2017–2026
88
Parents
145
Auto-summarization of audio-video presentations
Li-wei He, Elizabeth Sanocki, Anoop Gupta et al. · 1999 · 222 citations · Full text
MSMO: Multimodal Summarization with Multimodal Output
Junnan Zhu, Haoran Li, Tianshang Liu et al. · 2018 · 178 citations · Full text
Keep Meeting Summaries on Topic: Abstractive Multi-Modal Meeting Summarization
Manling Li, Lingyu Zhang, Heng Ji et al. · 2019 · 136 citations · Full text
Highlight sound effects detection in audio stream
Rui Cai, Lie Lu, Lianhong Cai · 2003 · 108 citations
1–5 of 145
477
8
h-index
8
h-index
7
h-index
7
h-index
5
h-index
1–5 of 477
177
University of Chinese Academy of Sciences
Beijing, China
12 h-index
47 publications
3K citations

Chinese Academy of Sciences
Beijing, China
7 h-index
29 publications
1.3K citations
Carnegie Mellon University
Pittsburgh, United States
7 h-index
12 publications
409 citations

Peking University
Beijing, China
6 h-index
14 publications
865 citations

Nankai University
Tianjin, China
5 h-index
14 publications
321 citations
National Technical University of Athens
Athens, Greece
5 h-index
25 publications
2.2K citations
National University of Singapore
Singapore, Singapore
5 h-index
11 publications
452 citations
Institute of Automation
Beijing, China
4 h-index
19 publications
1.4K citations
1–8 of 177
8 publications · 548 citations
8
h-index
Repository · 7 publications · 137 citations
7
h-index
Conference · 5 publications · 280 citations
5
h-index
3 publications · 109 citations
3
h-index
3 publications · 45 citations
3
h-index
1–5