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2 | Date | Title | Authors | Link | Read order | ||||||||||||||||||||

3 | From the Deep Learning Papers Reading Roadmap | https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap | |||||||||||||||||||||||

4 | 5/28/2015 | Deep learning | Yann LeCun, Yoshua Bengio, Geoffrey Hinton | http://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf | 1 | ||||||||||||||||||||

5 | 6/8/2006 | A fast learning algorithm for deep belief nets | Geoffrey Hinton, Simon Osindero, Yee-Whye Teh | http://www.cs.toronto.edu/~hinton/absps/ncfast.pdf | 2 | ||||||||||||||||||||

6 | 6/28/2006 | Reducing the dimensionality of data with neural networks | Geoffrey Hinton, Ruslan R. Salakhutdinov | http://www.cs.toronto.edu/~hinton/science.pdf | 3 | ||||||||||||||||||||

7 | 12/3/2012 | Imagenet classification with deep convolutional neural networks | Alex Krizhevsky, Ilya Sutskever, Geoffrey Hinton | http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf | 4 | ||||||||||||||||||||

8 | 9/4/2014 | Very deep convolutional networks for large-scale image recognition | Karen Simonyan, Andrew Zisserman | https://arxiv.org/abs/1409.1556v6 | 5 | ||||||||||||||||||||

9 | 12/16/2013 | Network In Network | Min Lin, Qiang Chen, Shuicheng Yan | https://arxiv.org/abs/1312.4400 | 6 | ||||||||||||||||||||

10 | 9/17/2014 | Going deeper with convolutions | Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich | https://arxiv.org/abs/1409.4842v1 | 7 | ||||||||||||||||||||

11 | 12/10/2015 | Deep residual learning for image recognition | Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun | https://arxiv.org/abs/1512.03385v1 | 8 | ||||||||||||||||||||

12 | 10/15/2012 | Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups | Geoffrey Hinton, et al. | http://cs224d.stanford.edu/papers/maas_paper.pdf | 9 | ||||||||||||||||||||

13 | 3/22/2013 | Speech recognition with deep recurrent neural networks | Alex Graves, Abdel-rahman Mohamed, Geoffrey Hinton | https://arxiv.org/abs/1303.5778v1 | 10 | ||||||||||||||||||||

14 | 6/21/2014 | Towards End-To-End Speech Recognition with Recurrent Neural Networks | Alex Graves, Navdeep Jaitly | http://www.jmlr.org/proceedings/papers/v32/graves14.pdf | 11 | ||||||||||||||||||||

15 | 7/24/2015 | Fast and accurate recurrent neural network acoustic models for speech recognition | Haşim Sak, et al. | https://arxiv.org/abs/1507.06947v1 | 12 | ||||||||||||||||||||

16 | 12/8/2015 | Deep speech 2: End-to-end speech recognition in english and mandarin | Dario Amodei, et al. | https://arxiv.org/abs/1512.02595v1 | 13 | ||||||||||||||||||||

17 | 10/17/2016 | Achieving Human Parity in Conversational Speech Recognition | W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig | https://arxiv.org/abs/1610.05256v2 | 14 | ||||||||||||||||||||

18 | 7/3/2012 | Improving neural networks by preventing co-adaptation of feature detectors | Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, Ruslan R. Salakhutdinov | https://arxiv.org/abs/1207.0580v1 | 15 | ||||||||||||||||||||

19 | 6/1/2014 | Dropout: a simple way to prevent neural networks from overfitting | Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov | https://www.cs.toronto.edu/~hinton/absps/JMLRdropout.pdf | 16 | ||||||||||||||||||||

20 | 2/11/2015 | Batch normalization: Accelerating deep network training by reducing internal covariate shift | Sergey Ioffe, Christian Szegedy | https://arxiv.org/abs/1502.03167v3 | 17 | ||||||||||||||||||||

21 | 7/21/2016 | Layer normalization | Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey Hinton | https://arxiv.org/abs/1607.06450v1 | 18 | ||||||||||||||||||||

22 | 2/9/2016 | Binarized Neural Networks: Training Neural Networks with Weights and Activations Constrained to+ 1 or−1 | Matthieu Courbariaux, Itay Hubara, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio | https://arxiv.org/abs/1602.02830v3 | 19 | ||||||||||||||||||||

23 | 8/18/2016 | Decoupled neural interfaces using synthetic gradients | Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero, Oriol Vinyals, Alex Graves, David Silver, Koray Kavukcuoglu | https://arxiv.org/abs/1608.05343v2 | 20 | ||||||||||||||||||||

24 | 11/18/2015 | Net2net: Accelerating learning via knowledge transfer | Tianqi Chen, Ian Goodfellow, Jonathon Shlens | https://arxiv.org/abs/1511.05641v4 | 21 | ||||||||||||||||||||

25 | 3/5/2016 | Network Morphism | Tao Wei, Changhu Wang, Yong Rui, Chang Wen Chen | https://arxiv.org/abs/1603.01670v2 | 22 | ||||||||||||||||||||

26 | 6/17/2013 | On the importance of initialization and momentum in deep learning | Ilya Sutskever, James Martens, George Dahl, Geoffrey Hinton | http://www.jmlr.org/proceedings/papers/v28/sutskever13.pdf | 23 | ||||||||||||||||||||

27 | 12/22/2014 | Adam: A method for stochastic optimization | Diederik Kingma, Jimmy Ba. | https://arxiv.org/abs/1412.6980v9 | 24 | ||||||||||||||||||||

28 | 6/14/2016 | Learning to learn by gradient descent by gradient descent | Marcin Andrychowicz, Misha Denil, Sergio Gomez, Matthew W. Hoffman, David Pfau, Tom Schaul, Brendan Shillingford, Nando de Freitas | https://arxiv.org/abs/1606.04474v2 | 25 | ||||||||||||||||||||

29 | 10/1/2015 | Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding | Song Han, Huizi Mao, William J. Dally | https://arxiv.org/abs/1510.00149v5 | 26 | ||||||||||||||||||||

30 | 2/24/2016 | SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 1MB model size | Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, Kurt Keutzer | https://arxiv.org/abs/1602.07360v4 | 27 | ||||||||||||||||||||

31 | 12/29/2011 | Building high-level features using large scale unsupervised learning | Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, Greg S. Corrado, Jeff Dean, Andrew Y. Ng | https://arxiv.org/abs/1112.6209v5 | 28 | ||||||||||||||||||||

32 | 12/20/2013 | Auto-encoding variational bayes | Diederik Kingma, Max Welling | https://arxiv.org/abs/1312.6114v10 | 29 | ||||||||||||||||||||

33 | 6/10/2014 | Generative adversarial nets | Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio | https://arxiv.org/abs/1406.2661v1 | 30 | ||||||||||||||||||||

34 | 11/19/2015 | Unsupervised representation learning with deep convolutional generative adversarial networks | Alec Radford, Luke Metz, and Soumith Chintala | https://arxiv.org/abs/1511.06434v2 | 31 | ||||||||||||||||||||

35 | 2/16/2015 | DRAW: A recurrent neural network for image generation | Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra | https://arxiv.org/abs/1502.04623v2 | 32 | ||||||||||||||||||||

36 | 1/25/2016 | Pixel recurrent neural networks | Aaron van den Oord, Nal Kalchbrenner, Koray Kavukcuoglu | https://arxiv.org/abs/1601.06759v3 | 33 | ||||||||||||||||||||

37 | 6/16/2016 | Conditional image generation with PixelCNN decoders | Aaron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, Koray Kavukcuoglu | https://arxiv.org/abs/1606.05328v2 | 34 | ||||||||||||||||||||

38 | 8/4/2013 | Generating sequences with recurrent neural networks | Alex Graves | https://arxiv.org/abs/1308.0850v5 | 35 | ||||||||||||||||||||

39 | 6/3/2014 | Learning phrase representations using RNN encoder-decoder for statistical machine translation | Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio | https://arxiv.org/abs/1406.1078v3 | 36 | ||||||||||||||||||||

40 | 9/10/2014 | Sequence to sequence learning with neural networks | Ilya Sutskever, Oriol Vinyals, Quoc V. Le | https://arxiv.org/abs/1409.3215v3 | 37 | ||||||||||||||||||||

41 | 9/1/2014 | Neural Machine Translation by Jointly Learning to Align and Translate | Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio | https://arxiv.org/abs/1409.0473v7 | 38 | ||||||||||||||||||||

42 | 6/19/2015 | A neural conversational model | Oriol Vinyals, Quoc Le | https://arxiv.org/abs/1506.05869v3 | 39 | ||||||||||||||||||||

43 | 10/20/2014 | Neural turing machines | Alex Graves, Greg Wayne, Ivo Danihelka | https://arxiv.org/abs/1410.5401v2 | 40 | ||||||||||||||||||||

44 | 5/4/2015 | Reinforcement Learning Neural Turing Machines | Wojciech Zaremba, Ilya Sutskever | http://arxiv.org/abs/1505.00521v3 | 41 | ||||||||||||||||||||

45 | 10/15/2014 | Memory networks | Jason Weston, Sumit Chopra, Antoine Bordes | http://arxiv.org/abs/1410.3916v11 | 42 | ||||||||||||||||||||

46 | 3/31/2015 | End-to-end memory networks | Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus | http://arxiv.org/abs/1503.08895v5 | 43 | ||||||||||||||||||||

47 | 6/9/2015 | Pointer networks | Oriol Vinyals, Meire Fortunato, Navdeep Jaitly | http://arxiv.org/abs/1506.03134v2 | 44 | ||||||||||||||||||||

48 | 10/27/2016 | Hybrid computing using a neural network with dynamic external memory | Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwińska, Sergio Gómez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John Agapiou, Adrià Puigdomènech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, Demis Hassabis | https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=2ahUKEwiymei-v6_gAhVGilQKHearAmUQFjAAegQIChAB&url=https%3A%2F%2Fwww.nature.com%2Farticles%2Fnature20101&usg=AOvVaw2IdzkvQUIO84KRHmXHhgAe | 45 | ||||||||||||||||||||

49 | 12/19/2013 | Playing atari with deep reinforcement learning | Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller | https://arxiv.org/abs/1312.5602v1 | 46 | ||||||||||||||||||||

50 | 2/26/2015 | Human-level control through deep reinforcement learning | Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis | https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=2ahUKEwiw4PaJwK_gAhWmiVQKHYLiAV0QFjAAegQICRAC&url=https%3A%2F%2Fweb.stanford.edu%2Fclass%2Fpsych209%2FReadings%2FMnihEtAlHassibis15NatureControlDeepRL.pdf&usg=AOvVaw0uqHxqo8Yyn3cmySQWqe8Z | 47 | ||||||||||||||||||||

51 | 11/20/2015 | Dueling network architectures for deep reinforcement learning | Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas | http://arxiv.org/abs/1511.06581v3 | 48 | ||||||||||||||||||||

52 | 2/4/2016 | Asynchronous methods for deep reinforcement learning | Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu | http://arxiv.org/abs/1602.01783v2 | 49 | ||||||||||||||||||||

53 | 9/9/2015 | Continuous control with deep reinforcement learning | Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra | http://arxiv.org/abs/1509.02971v5 | 50 | ||||||||||||||||||||

54 | 3/2/2016 | Continuous Deep Q-Learning with Model-based Acceleration | Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine | http://arxiv.org/abs/1603.00748v1 | 51 | ||||||||||||||||||||

55 | 2/19/2015 | Trust region policy optimization | John Schulman, Sergey Levine, Philipp Moritz, Michael I. Jordan, Pieter Abbeel | http://arxiv.org/abs/1502.05477v5 | 52 | ||||||||||||||||||||

56 | 1/1/2016 | Mastering the game of Go with deep neural networks and tree search | David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis | https://storage.googleapis.com/deepmind-media/alphago/AlphaGoNaturePaper.pdf | 53 | ||||||||||||||||||||

57 | 7/2/2011 | Deep Learning of Representations for Unsupervised and Transfer Learning | Yoshua Bengio | http://www.jmlr.org/proceedings/papers/v27/bengio12a/bengio12a.pdf | 54 | ||||||||||||||||||||

58 | 3/15/2013 | Lifelong Machine Learning Systems: Beyond Learning Algorithms | Daniel L. Silver, Qiang Yang, Lianghao Li | http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.696.7800&rep=rep1&type=pdf | 55 | ||||||||||||||||||||

59 | 3/9/3015 | Distilling the knowledge in a neural network | Geoffrey Hinton, Oriol Vinyals, Jeff Dean | https://arxiv.org/abs/1503.02531v1 | 56 | ||||||||||||||||||||

60 | 11/19/2015 | Policy distillation | Andrei A. Rusu, Sergio Gomez Colmenarejo, Caglar Gulcehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell | http://arxiv.org/abs/1511.06295v2 | 57 | ||||||||||||||||||||

61 | 11/29/2015 | Actor-mimic: Deep multitask and transfer reinforcement learning | Emilio Parisotto, Jimmy Lei Ba, Ruslan Salakhutdinov | http://arxiv.org/abs/1511.06342v4 | 58 | ||||||||||||||||||||

62 | 6/15/2016 | Progressive neural networks | Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, Raia Hadsell | http://arxiv.org/abs/1606.04671v3 | 59 | ||||||||||||||||||||

63 | 12/11/2015 | Human-level concept learning through probabilistic program induction | Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum | http://clm.utexas.edu/compjclub/wp-content/uploads/2016/02/lake2015.pdf | 60 | ||||||||||||||||||||

64 | 6/6/2015 | Siamese Neural Networks for One-shot Image Recognition | Gregory Koch, Richard Zemel, Ruslan Salakhutdinov | http://www.cs.utoronto.ca/~gkoch/files/msc-thesis.pdf | 61 | ||||||||||||||||||||

65 | 5/19/2016 | One-shot Learning with Memory-Augmented Neural Networks | Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap | http://arxiv.org/abs/1605.06065v1 | 62 | ||||||||||||||||||||

66 | 6/13/2016 | Matching Networks for One Shot Learning | Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, Daan Wierstra | http://arxiv.org/abs/1606.04080v2 | 63 | ||||||||||||||||||||

67 | 6/9/2016 | Low-shot Visual Recognition by Shrinking and Hallucinating Features | Bharath Hariharan, Ross Girshick | http://arxiv.org/abs/1606.02819v4 | 64 | ||||||||||||||||||||

68 | 4/21/2012 | Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing | Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio | https://www.hds.utc.fr/~bordesan/dokuwiki/lib/exe/fetch.php?id=en%3Apubli&cache=cache&media=en:bordes12aistats.pdf | 65 | ||||||||||||||||||||

69 | 10/16/2013 | Distributed representations of words and phrases and their compositionality | Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean | http://arxiv.org/abs/1310.4546v1 | 66 | ||||||||||||||||||||

70 | 6/24/2015 | Ask Me Anything: Dynamic Memory Networks for Natural Language Processing | Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher | http://arxiv.org/abs/1506.07285v5 | 67 | ||||||||||||||||||||

71 | 7/26/2015 | Character-Aware Neural Language Models | Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush | http://arxiv.org/abs/1508.06615v4 | 68 | ||||||||||||||||||||

72 | 2/19/2015 | Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks | Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M. Rush, Bart van Merriënboer, Armand Joulin, Tomas Mikolov | http://arxiv.org/abs/1502.05698v10 | 69 | ||||||||||||||||||||

73 | 6/10/2015 | Teaching Machines to Read and Comprehend | Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom | http://arxiv.org/abs/1506.03340v3 | 70 | ||||||||||||||||||||

74 | 6/6/2016 | Very Deep Convolutional Networks for Text Classification | Alexis Conneau, Holger Schwenk, Loïc Barrault, Yann Lecun | http://arxiv.org/abs/1606.01781v2 | 71 | ||||||||||||||||||||

75 | 6/6/2016 | Bag of Tricks for Efficient Text Classification | Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov | http://arxiv.org/abs/1607.01759v3 | 72 | ||||||||||||||||||||

76 | 12/5/2013 | Deep neural networks for object detection | Christian Szegedy, Alexander Toshev, Dumitru Erhan | http://papers.nips.cc/paper/5207-deep-neural-networks-for-object-detection.pdf | 73 | ||||||||||||||||||||

77 | 11/11/2013 | Rich feature hierarchies for accurate object detection and semantic segmentation | Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik | http://arxiv.org/abs/1311.2524v5 | 74 | ||||||||||||||||||||

78 | 6/18/2014 | Spatial pyramid pooling in deep convolutional networks for visual recognition | Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun | http://arxiv.org/abs/1406.4729v4 | 75 | ||||||||||||||||||||

79 | 4/30/2015 | Fast R-CNN | Ross Girshick | http://arxiv.org/abs/1504.08083v2 | 76 | ||||||||||||||||||||

80 | 6/4/2015 | Faster R-CNN: Towards real-time object detection with region proposal networks | Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun | http://arxiv.org/abs/1506.01497v3 | 77 | ||||||||||||||||||||

81 | 6/8/2015 | You only look once: Unified, real-time object detection | Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi | http://arxiv.org/abs/1506.02640v5 | 78 | ||||||||||||||||||||

82 | 12/8/2015 | SSD: Single Shot MultiBox Detector | Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg | http://arxiv.org/abs/1512.02325v5 | 79 | ||||||||||||||||||||

83 | 5/20/2016 | R-FCN: Object Detection via Region-based Fully Convolutional Networks | Jifeng Dai, Yi Li, Kaiming He, Jian Sun | http://arxiv.org/abs/1605.06409v2 | 80 | ||||||||||||||||||||

84 | 11/14/2014 | Fully convolutional networks for semantic segmentation | Jonathan Long, Evan Shelhamer, Trevor Darrell | http://arxiv.org/abs/1411.4038v2 | 81 | ||||||||||||||||||||

85 | 12/22/2014 | Semantic image segmentation with deep convolutional nets and fully connected crfs | Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille | http://arxiv.org/abs/1412.7062v4 | 82 | ||||||||||||||||||||

86 | 6/20/2015 | Learning to segment object candidates | Pedro O. Pinheiro, Ronan Collobert, Piotr Dollar | http://arxiv.org/abs/1506.06204v2 | 83 | ||||||||||||||||||||

87 | 12/14/2015 | Instance-aware semantic segmentation via multi-task network cascades | Jifeng Dai, Kaiming He, Jian Sun | http://arxiv.org/abs/1512.04412v1 | 84 | ||||||||||||||||||||

88 | 3/29/2016 | Instance-sensitive Fully Convolutional Networks | Jifeng Dai, Kaiming He, Yi Li, Shaoqing Ren, Jian Sun | http://arxiv.org/abs/1603.08678v1 | 85 | ||||||||||||||||||||

89 | 3/20/2017 | Mask R-CNN | Kaiming He, Georgia Gkioxari, Piotr Dollár, Ross Girshick | http://arxiv.org/abs/1703.06870v3 | 86 | ||||||||||||||||||||

90 | 12/5/2013 | Learning a deep compact image representation for visual tracking | Naiyan Wang, Dit-Yan Yeung | http://papers.nips.cc/paper/5192-learning-a-deep-compact-image-representation-for-visual-tracking.pdf | 87 | ||||||||||||||||||||

91 | 1/19/2015 | Transferring rich feature hierarchies for robust visual tracking | Naiyan Wang, Siyi Li, Abhinav Gupta, Dit-Yan Yeung | http://arxiv.org/abs/1501.04587v2 | 88 | ||||||||||||||||||||

92 | 12/1/2015 | Visual tracking with fully convolutional networks | Lijun Wang, et al. | http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Wang_Visual_Tracking_With_ICCV_2015_paper.pdf | 89 | ||||||||||||||||||||

93 | 4/6/2016 | Learning to Track at 100 FPS with Deep Regression Networks | David Held, Sebastian Thrun, Silvio Savarese | http://arxiv.org/abs/1604.01802v2 | 90 | ||||||||||||||||||||

94 | 6/30/2016 | Fully-Convolutional Siamese Networks for Object Tracking | Luca Bertinetto, Jack Valmadre, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr | http://arxiv.org/abs/1606.09549v2 | 91 | ||||||||||||||||||||

95 | 7/12/2016 | Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking | Martin Danelljan, Andreas Robinson, Fahad Shahbaz Khan, Michael Felsberg | http://arxiv.org/abs/1608.03773v2 | 92 | ||||||||||||||||||||

96 | 7/25/2016 | Modeling and Propagating CNNs in a Tree Structure for Visual Tracking | Hyeonseob Nam, Mooyeol Baek, Bohyung Han | http://arxiv.org/abs/1608.07242v1 | 93 | ||||||||||||||||||||

97 | 11/15/2010 | Every picture tells a story: Generating sentences from images | Ali Farhadi, et al. | https://www.cs.cmu.edu/~afarhadi/papers/sentence.pdf | 94 | ||||||||||||||||||||

98 | 6/20/2011 | Baby talk: Understanding and generating image descriptions | Girish Kulkarni, et al. | http://tamaraberg.com/papers/generation_cvpr11.pdf | 95 | ||||||||||||||||||||

99 | 11/17/2014 | Show and tell: A neural image caption generator | Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan | http://arxiv.org/abs/1411.4555v2 | 96 | ||||||||||||||||||||

100 | 11/17/2014 | Long-term recurrent convolutional networks for visual recognition and description | Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, Trevor Darrell | http://arxiv.org/abs/1411.4389v4 | 97 |

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