Multimodal Event Detection
Multimodal Event Detection is an event detection paradigm that integrates and analyzes complementary information from multiple modalities—such as text, image, audio, and video—to identify and classify events in a unified semantic space, distinguishing it from unimodal approaches by leveraging cross-modal correlations for improved detection accuracy and contextual understanding.
301
Publications
14.1K
Citations
1.1K
Authors
366
Institutions
Publications per year
2017–2026
132
Parents
301
Yaqing Wang, Fenglong Ma, Zhiwei Jin et al. · 2018 · 1.1K citations · Full text
Detecting Events and Key Actors in Multi-person Videos
Vignesh Ramanathan, Jonathan Huang, Sami Abu-El-Haija et al. · 2016 · 224 citations
Dual Attention Matching for Audio-Visual Event Localization
Yu Wu, Linchao Zhu, Yan Yan et al. · 2019 · 221 citations · Full text
Multi-modal Knowledge-aware Event Memory Network for Social Media Rumor Detection
Huaiwen Zhang, Quan Fang, Shengsheng Qian et al. · 2019 · 200 citations
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366
Institute for Infocomm Research
Singapore, Singapore
12 h-index
39 publications
2.1K citations

Chinese Academy of Sciences
Beijing, China
12 h-index
41 publications
2.3K citations
Carnegie Mellon University
Pittsburgh, United States
11 h-index
36 publications
1.7K citations
National University of Singapore
Singapore, Singapore
10 h-index
26 publications
1.4K citations
Nanyang Technological University
Singapore, Singapore
9 h-index
16 publications
789 citations
University of Illinois Urbana-Champaign
Urbana, United States
9 h-index
29 publications
2K citations
Institute of Automation
Beijing, China
8 h-index
26 publications
1.2K citations
SRI International
Menlo Park, United States
6 h-index
24 publications
507 citations
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9 publications · 638 citations
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Repository · 6 publications · 289 citations
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Conference · 5 publications · 232 citations
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6 publications · 92 citations
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5 publications · 318 citations
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