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Visual question answering (or VQA) is a new and exciting problem that combines natural language processing and computer vision techniques.
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A multi-world approach to question answering about real-world scenes based on uncertain input
Mateusz Malinowski and Mario Fritz. 2014 · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Are you talking to a machine? dataset and methods for multilingual image question
Haoyuan Gao, Junhua Mao, Jie Zhou, Zhiheng Huang, Lei Wang, and Wei Xu. 2015 · 2015
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Deep compositional question answering with neural module networks
Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein. 2016 · 2016
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Answer-type prediction for visual question answering
Kushal Kafle and Christopher Kanan. 2016 · 2016
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Hierarchical question-image co-attention for visual question answering
Jiasen Lu, Jianwei Yang, Dhruv Batra, and Devi Parikh. 2016 · 2016
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Ask your neurons: A deep learning approach to visual question answering
Mateusz Malinowski, Marcus Rohrbach, and Mario Fritz. 2016 · 2016
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Image question answering using convolutional neural network with dynamic parameter prediction
Hyeonwoo Noh, Paul Hongsuck Seo, and Bohyung Han. 2016 · 2016
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Lin Ma, Zhengdong Lu, and Hang Li. 2015 · 2015
Cited alongside, same era.
Exploring models and data for image question answering
Mengye Ren, Ryan Kiros, and Richard Zemel. 2015 · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. 2015 · 2015
Cited alongside, same era.
Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C Courville, Ruslan Salakhutdinov, Richard S Zemel, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
Visual madlibs: Fill in the blank description generation and question answering
Licheng Yu, Eunbyung Park, Alexander C Berg, and Tamara L Berg. 2015 · 2015
Cited alongside, same era.
Simple baseline for visual question answering
Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, and Rob Fergus. 2015 · 2015
Cited alongside, same era.
Visual question answering: A survey of methods and datasets
Qi Wu, Damien Teney, Peng Wang, Chunhua Shen, Anthony Dick, and Anton van den Hengel. 2016a
Cited in the paper.
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2016 · 2016
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Where to look: Focus regions for visual question answering
Kevin J Shih, Saurabh Singh, and Derek Hoiem. 2016 · 2016
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Dynamic coattention networks for question answering
Caiming Xiong, Victor Zhong, and Richard Socher. 2016 · 2016
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Stacked attention networks for image question answering
Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, and Alex Smola. 2016 · 2016
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Visual7w: Grounded question answering in images
Yuke Zhu, Oliver Groth, Michael Bernstein, and Li Fei-Fei. 2016 · 2016
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