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The success of deep learning research has catapulted deep models into production systems that our society is becoming increasingly dependent on, especially in the image and video domains.
Convolutional two-stream network fusion for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Andrew Zisserman · 1941
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Two-frame motion estimation based on polynomial expansion
Gunnar Farnebäck · 2003
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A duality based approach for realtime tv-l1 optical flow
C. Zach, T. Pock, and H. Bischof · 2007
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3d convolutional neural networks for human action recognition
Shuiwang Ji, Wei Xu, Ming Yang, and Kai Yu · 2012
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Ucf101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, and Rob Fergus · 2013
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TV-L1 Optical Flow Estimation
Javier Sánchez Pérez, Enric Meinhardt-Llopis, and Gabriele Facciolo · 2013
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Explaining and Harnessing Adversarial Examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2014
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Large-scale video classification with convolutional neural networks
Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei · 2014
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Two-stream convolutional networks for action recognition in videos
Karen Simonyan and Andrew Zisserman · 2014
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Flownet: Learning optical flow with convolutional networks
Philipp Fischer, Alexey Dosovitskiy, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Beyond short snippets: Deep networks for video classification
Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, and George Toderici · 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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Adversarial machine learning at scale
Alexey Kurakin, Ian J. Goodfellow, and Samy Bengio · 2016
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Delving into transferable adversarial examples and black-box attacks
Yanpei Liu, Xinyun Chen, Chang Liu, and Dawn Song · 2016
Cited alongside, same era.
Quo vadis, action recognition? a new model and the kinetics dataset
João Carreira and Andrew Zisserman · 2017
Later among the works it cites.
Spatiotemporal multiplier networks for video action recognition
C. Feichtenhofer, A. Pinz, and R. P. Wildes · 2017
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Actionvlad: Learning spatio-temporal aggregation for action classification
Rohit Girdhar, Deva Ramanan, Abhinav Gupta, Josef Sivic, and Bryan C. Russell · 2017
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Flownet 2.0: Evolution of optical flow estimation with deep networks
Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, and Thomas Brox · 2017
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flownet2-pytorch: Pytorch implementation of flownet 2.0: Evolution of optical flow estimation with deep networks
Fitsum Reda, Robert Pottorff, Jon Barker, and Bryan Catanzaro · 2017
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Deepfool: A simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard · 2016
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The limitations of deep learning in adversarial settings
Nicolas Papernot, Patrick D. McDaniel, Somesh Jha, Matt Fredrikson, Z. Berkay Celik, and Ananthram Swami · 2016
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An analysis of convolutional long short-term memory recurrent neural networks for gesture recognition
Eleni Tsironi, Pablo Barros, Cornelius Weber, and Stefan Wermter · 2016
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Temporal segment networks: Towards good practices for deep action recognition
Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, and Luc Van Gool · 2016
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Towards evaluating the robustness of neural networks
Nicholas Carlini and David A. Wagner · 2017
Cited alongside, same era.
Spatiotemporal residual networks for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Richard P. Wildes
Cited in the paper.
Transferability in machine learning: from phenomena to black-box attacks using adversarial samples
Nicolas Papernot, Patrick D. McDaniel, and Ian J. Goodfellow
Cited in the paper.
Laura Sevilla-Lara, Yiyi Liao, Fatma Güney, Varun Jampani, Andreas Geiger, and Michael J. Black · 2017
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Asynchronous temporal fields for action recognition
Gunnar A. Sigurdsson, Santosh Kumar Divvala, Ali Farhadi, and Abhinav Gupta · 2017
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The Space of Transferable Adversarial Examples
F. Tramèr, N. Papernot, I. Goodfellow, D. Boneh, and P. McDaniel · 2017
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Videolstm convolves, attends and flows for action recognition
Zhenyang Li, Efstratios Gavves, Mihir Jain, and Cees Snoek · 2018
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Long-term temporal convolutions for action recognition
Gul Varol, Ivan Laptev, and Cordelia Schmid · 2018
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