Video-Based Misinformation Detection is a computational framework designed to identify false or misleading content specifically within video data by analyzing multimodal signals such as visual, auditory, and textual elements, distinguishing it from broader misinformation detection approaches that may focus on text or images alone.
50
Publications
2.5K
Citations
186
Authors
60
Institutions
Publications per year
2017–2026
50
Parents
Publications
50
1–5 of 50
Authors
186
- JC
3
h-index
- YK
2
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- PQ
2
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- TC
2
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- WJ
2
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1–5 of 186
Institutions
60
National University of Singapore
Singapore, Singapore
3 h-index
10 publications
715 citations
Institute of Computing Technology
Beijing, China
3 h-index
12 publications
638 citations
Chinese Academy of Sciences
Beijing, China
3 h-index
7 publications
288 citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
8 publications
437 citations
Nanyang Technological University
Singapore, Singapore
2 h-index
6 publications
100 citations
New York University
New York, United States
2 h-index
4 publications
122 citations
Binghamton University
Binghamton, United States
2 h-index
4 publications
1.5K citations
Sungkyunkwan University
Seoul, South Korea
2 h-index
4 publications
144 citations
1–8 of 60
Venues
- Proceedings of the International AAAI Conference on Web and Social Media
2 publications · 55 citations
2
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- arXiv (Cornell University)
Repository · 1 publications · 13 citations
2
h-index
- 2021 IEEE International Conference on Big Data (Big Data)
Conference · 1 publications · 97 citations
1
h-index
- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 1 publications · 493 citations
1
h-index
- 2021 International Congress of Advanced Technology and Engineering (ICOTEN)
1 publications · 20 citations
1
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1–5