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Video question answering (VideoQA) is designed to answer a given question based on a relevant video clip.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Freebase: A collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor · 2008
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Deep face recognition
Omkar M Parkhi, Andrea Vedaldi, and Andrew Zisserman · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Faster r-cnn: towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2016
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Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch · 2016
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Ask me anything: Free-form visual question answering based on knowledge from external sources
Qi Wu, Peng Wang, Chunhua Shen, Anthony Dick, and Anton Van Den Hengel · 2016
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ConceptnNet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Unifying the video and question attentions for open-ended video question answering
Hongyang Xue, Zhou Zhao, and Deng Cai · 2017
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Video question answering via attribute-augmented attention network learning
Yunan Ye, Zhou Zhao, Yimeng Li, Long Chen, Jun Xiao, and Yueting Zhuang · 2017
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Video question answering via hierarchical spatio-temporal attention networks
Zhou Zhao, Qifan Yang, Deng Cai, Xiaofei He, and Yueting Zhuang · 2017
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Cross-dataset adaptation for visual question answering
Wei-Lun Chao, Hexiang Hu, and Fei Sha · 2018
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Hierarchical relational attention for video question answering
Muhammad Iqbal Hasan Chowdhury, Kien Nguyen, Sridha Sridharan, and Clinton Fookes · 2018
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Knowledge-based video question answering with unsupervised scene descriptions
Noa Garcia and Yuta Nakashima · 2020
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KnowIT VQA: Answering knowledge-based questions about videos
Noa Garcia, Mayu Otani, Chenhui Chu, and Yuta Nakashima · 2020
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Location-aware graph convolutional networks for video question answering
Deng Huang, Peihao Chen, Runhao Zeng, Qing Du, Mingkui Tan, and Chuang Gan · 2020
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Stanza: A Python natural language processing toolkit for many human languages
Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, and Christopher D Manning · 2020
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Hexiang Hu, Wei-Lun Chao, and Fei Sha · 2018
Cited alongside, same era.
TVQA: Localized, compositional video question answering
Jie Lei, Licheng Yu, Mohit Bansal, and Tamara L Berg · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
OK-VQA: A visual question answering benchmark requiring external knowledge
Kenneth Marino, Mohammad Rastegari, Ali Farhadi, and Roozbeh Mottaghi · 2019
Cited alongside, same era.
Transfer learning via unsupervised task discovery for visual question answering
Hyeonwoo Noh, Taehoon Kim, Jonghwan Mun, and Bohyung Han · 2019
Cited alongside, same era.
A picture may be worth a hundred words for visual question answering
Yusuke Hirota, Noa Garcia, Mayu Otani, Chenhui Chu, Yuta Nakashima, Ittetsu Taniguchi, and Takao Onoye
Cited in the paper.
Visual question answering with textual representations for images
Yusuke Hirota, Noa Garcia, Mayu Otani, Chenhui Chu, Yuta Nakashima, Ittetsu Taniguchi, and Takao Onoye
Cited in the paper.
Open-ended visual question answering by multi-modal domain adaptation
Yiming Xu, Lin Chen, Zhongwei Cheng, Lixin Duan, and Jiebo Luo · 2020
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BERT representations for video question answering
Zekun Yang, Noa Garcia, Chenhui Chu, Mayu Otani, Yuta Nakashima, and Haruo Takemura · 2020
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iPerceive: Applying common-sense reasoning to multi-modal dense video captioning and video question answering
Aman Chadha, Gurneet Arora, and Navpreet Kaloty · 2021
Closest in time.
On the hidden treasure of dialog in video question answering
Deniz Engin, François Schnitzler, Ngoc QK Duong, and Yannis Avrithis · 2021
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