Visual Question Answering
Visual Question Answering is a multidisciplinary task in computer vision and natural language processing that requires a system to generate accurate and contextually appropriate answers to natural language questions based on the content of a given image.
2.9K
Publications
257.4K
Citations
8.8K
Authors
1.4K
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Publications per year
2017–2026
2.4K
2.9K
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das et al. · 2017 · 21.6K citations
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Kelvin Xu, Jimmy Ba, Ryan Kiros et al. · arXiv (Cornell University) · 2015 · 7.5K citations · Full text
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
Peter Anderson, Xiaodong He, Chris Buehler et al. · 2018 · 5.1K citations
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Carnegie Mellon University
Pittsburgh, United States
40 h-index
154 publications
19.6K citations

Chinese Academy of Sciences
Beijing, China
40 h-index
252 publications
13.9K citations

The University of Adelaide
Adelaide, Australia
38 h-index
155 publications
23.8K citations
Google (United States)
Mountain View, United States
36 h-index
246 publications
25.7K citations
University of Chinese Academy of Sciences
Beijing, China
35 h-index
177 publications
8.9K citations
Stanford University
Stanford, United States
34 h-index
134 publications
56.9K citations
Tsinghua University
Beijing, China
33 h-index
175 publications
11.7K citations
Microsoft (United States)
Redmond, United States
33 h-index
148 publications
32.7K citations
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Repository · 497 publications · 47.4K citations
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Conference · 80 publications · 8.3K citations
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55 publications · 2.8K citations
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73 publications · 2.9K citations
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31 publications · 2.2K citations
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