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We present LLoVi, a language-based framework for long-range video question-answering (LVQA).
Language models are few-shot learners
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The curious case of neural text degeneration
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Videograph: Recognizing minutes-long human activities in videos
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What gives the answer away? question answering bias analysis on video qa datasets
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Diederik P. Kingma and Jimmy Ba. 2014 · 2014
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Movieqa: Understanding stories in movies through question-answering
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Tvqa: Localized, compositional video question answering
Jie Lei, Licheng Yu, Mohit Bansal, and Tamara L Berg. 2018 · 2018
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Are we asking the right questions in movieqa?
Bhavan Jasani, Rohit Girdhar, and Deva Ramanan. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Long-term feature banks for detailed video understanding
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan, Kaiming He, Philipp Krahenbuhl, and Ross Girshick. 2019 · 2019
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Activitynet-qa: A dataset for understanding complex web videos via question answering
Zhou Yu, Dejing Xu, Jun Yu, Ting Yu, Zhou Zhao, Yueting Zhuang, and Dacheng Tao. 2019 · 2019
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Memory enhanced global-local aggregation for video object detection
Yihong Chen, Yue Cao, Han Hu, and Liwei Wang. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Is space-time attention all you need for video understanding?
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Dramaqa: Character-centered video story understanding with hierarchical QA
Seongho Choi, Kyoung-Woon On, Yu-Jung Heo, Ahjeong Seo, Youwon Jang, Min Su Lee, and Byoung-Tak Zhang. 2021 · 2021
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Tsu-Jui Fu, Linjie Li, Zhe Gan, Kevin Lin, William Yang Wang, Lijuan Wang, and Zicheng Liu. 2021 · 2021
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Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Ré. 2021 · 2021
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Video prediction recalling long-term motion context via memory alignment learning
Sangmin Lee, Hak Gu Kim, Dae Hwi Choi, Hyung-Il Kim, and Yong Man Ro. 2021 · 2021
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Less is more: Clipbert for video-and-language learningvia sparse sampling
Jie Lei, Linjie Li, Luowei Zhou, Zhe Gan, Tamara L. Berg, Mohit Bansal, and Jingjing Liu. 2021 · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021 · 2021
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Supervoxel attention graphs for long-range video modeling
Yang Wang, Gedas Bertasius, Tae-Hyun Oh, Abhinav Gupta, Minh Hoai, and Lorenzo Torresani. 2021 · 2021
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Next-qa: Next phase of question-answering to explaining temporal actions
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