Fetching the paper…
Reading the bibliography…
The convolution layer has been the dominant feature extractor in computer vision for years.
Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
K. Fukushima · 1980
Earlier work this paper cites.
Recognition-by-components: a theory of human image understanding
I. Biederman · 1987
Earlier work this paper cites.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
Earlier work this paper cites.
On Language: On the Diversity of Human Language Construction and Its Influence on the Mental Development of the Human Species
W. von Humboldt · 1999
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
M. Lin, Q. Chen, and S. Yan · 2013
Earlier work this paper cites.
Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
Earlier work this paper cites.
Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
Earlier work this paper cites.
Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Dynamic filter networks
X. Jia, B. De Brabandere, T. Tuytelaars, and L. V. Gool · 2016
Cited alongside, same era.
Geometric deep learning: going beyond euclidean data
M. M. Bronstein, J. Bruna, Y. LeCun, A. Szlam, and P. Vandergheynst · 2017
Cited alongside, same era.
Xception: Deep learning with depthwise separable convolutions
F. Chollet · 2017
Cited alongside, same era.
Deformable convolutional networks
J. Dai, H. Qi, Y. Xiong, Y. Li, G. Zhang, H. Hu, and Y. Wei · 2017
Cited alongside, same era.
Accurate, large minibatch sgd: Training imagenet in 1 hour
P. Goyal, P. Dollár, R. Girshick, P. Noordhuis, L. Wesolowski, A. Kyrola, A. Tulloch, Y. Jia, and K. He · 2017
Cited alongside, same era.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
Relational inductive biases, deep learning, and graph networks
P. W. Battaglia, J. B. Hamrick, V. Bapst, A. Sanchez-Gonzalez, V. Zambaldi, M. Malinowski, A. Tacchetti, D. Raposo, A. Santoro, R. Faulkner, et al · 2018
Later among the works it cites.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2018
Later among the works it cites.
Matrix capsules with em routing
G. E. Hinton, S. Sabour, and N. Frosst · 2018
Later among the works it cites.
Relation networks for object detection
H. Hu, J. Gu, Z. Zhang, J. Dai, and Y. Wei · 2018
Later among the works it cites.
H. Kannan, A. Kurakin, and I. Goodfellow · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam · 2017
Cited alongside, same era.
Active convolution: Learning the shape of convolution for image classification
Y. Jeon and J. Kim · 2017
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2017
Cited alongside, same era.
Dynamic routing between capsules
S. Sabour, N. Frosst, and G. E. Hinton · 2017
Cited alongside, same era.
Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
Cited alongside, same era.
Aggregated residual transformations for deep neural networks
S. Xie, R. Girshick, P. Dollár, Z. Tu, and K. He · 2017
Cited alongside, same era.
Shufflenet v2: Practical guidelines for efficient cnn architecture design
N. Ma, X. Zhang, H.-T. Zheng, and J. Sun · 2018
Later among the works it cites.
Deep learning: A critical appraisal
G. Marcus · 2018
Later among the works it cites.
Non-local neural networks
X. Wang, R. Girshick, A. Gupta, and K. He · 2018
Later among the works it cites.
Deep nets: What have they ever done for vision?
A. L. Yuille and C. Liu · 2018
Later among the works it cites.
Deformable convnets v2: More deformable, better results
X. Zhu, H. Hu, S. Lin, and J. Dai · 2018
Later among the works it cites.