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Self-supervised learning has become increasingly important to leverage the abundance of unlabeled data available on platforms like YouTube.
End-to-end dense video captioning with masked transformer
Luowei Zhou, Yingbo Zhou, Jason J. Corso, Richard Socher, and Caiming Xiong · 1904
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Baby talk: Understanding and generating image descriptions
Girish Kulkarni, Visruth Premraj, Sagnik Dhar, Siming Li, Yejin Choi, Alexander C Berg, and Tamara L Berg · 2011
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2014
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Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei · 2015
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What’s cookin’? interpreting cooking videos using text, speech and vision
Jonathan Malmaud, Jonathan Huang, Vivek Rathod, Nick Johnston, Andrew Rabinovich, and Kevin Murphy · 2015
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Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Unsupervised learning from narrated instruction videos
Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, and Simon Lacoste-Julien · 2016
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Soundnet: Learning sound representations from unlabeled video
Yusuf Aytar, Carl Vondrick, and Antonio Torralba · 2016
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Deep multi-scale video prediction beyond mean square error
Michael Mathieu, Camille Couprie, and Yann LeCun · 2016
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Shuffle and learn: unsupervised learning using temporal order verification
Ishan Misra, C Lawrence Zitnick, and Martial Hebert · 2016
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Visually indicated sounds
Andrew Owens, Phillip Isola, Josh McDermott, Antonio Torralba, Edward H Adelson, and William T Freeman · 2016
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Ambient sound provides supervision for visual learning
Andrew Owens, Jiajun Wu, Josh H McDermott, William T Freeman, and Antonio Torralba · 2016
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Anticipating visual representations from unlabeled video
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
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Generating videos with scene dynamics
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
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An uncertain future: Forecasting from static images using variational autoencoders
Jacob Walker, Carl Doersch, Abhinav Gupta, and Martial Hebert · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al · 2016
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Visual dynamics: Probabilistic future frame synthesis via cross convolutional networks
Tianfan Xue, Jiajun Wu, Katherine Bouman, and Bill Freeman · 2016
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AVA: A video dataset of spatio-temporally localized atomic visual actions
Chunhui Gu, Chen Sun, David A Ross, Carl Vondrick, Caroline Pantofaru, Yeqing Li, Sudheendra Vijayanarasimhan, George Toderici, Susanna Ricco, Rahul Sukthankar, et al · 2018
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Stochastic adversarial video prediction
Alex X Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine · 2018
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Neural baby talk
Jiasen Lu, Jianwei Yang, Dhruv Batra, and Devi Parikh · 2018
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Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer · 2018
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Deep unsupervised learning
Marc Aurelio Ranzato and Alex Graves · 2018
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MoCoGAN: Decomposing motion and content for video generation
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Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, et al · 2017
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Dense-Captioning events in videos
Ranjay Krishna, Kenji Hata, Frederic Ren, Li Fei-Fei, and Juan Carlos Niebles · 2017
Cited alongside, same era.
Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Slac: A sparsely labeled dataset for action classification and localization
Hang Zhao, Zhicheng Yan, Heng Wang, Lorenzo Torresani, and Antonio Torralba · 2017
Cited alongside, same era.
Stochastic variational video prediction
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H Campbell, and Sergey Levine · 2018
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Stochastic video generation with a learned prior
Emily Denton and Rob Fergus · 2018
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Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
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Rethinking spatiotemporal feature learning for video understanding
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy · 2018
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Weakly-supervised video object grounding from text by loss weighting and object interaction
Luowei Zhou, Nathan Louis, and Jason J Corso · 2018
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Towards automatic learning of procedures from web instructional videos
Luowei Zhou, Chenliang Xu, and Jason J Corso · 2018
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Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau · 2019
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Moments in time dataset: one million videos for event understanding
Mathew Monfort, Alex Andonian, Bolei Zhou, Kandan Ramakrishnan, Sarah Adel Bargal, Yan Yan, Lisa Brown, Quanfu Fan, Dan Gutfreund, Carl Vondrick, et al · 2019
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COIN: A large-scale dataset for comprehensive instructional video analysis
Yansong Tang, Dajun Ding, Yongming Rao, Yu Zheng, Danyang Zhang, Lili Zhao, Jiwen Lu, and Jie Zhou · 2019
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