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We present a simple and general method to train a single neural network executable at different widths (number of channels in a layer), permitting instant and adaptive accuracy-efficiency trade-offs at runtime.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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Fitnets: Hints for thin deep nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
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Impatient dnns-deep neural networks with dynamic time budgets
Manuel Amthor, Erik Rodner, and Joachim Denzler · 2016
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2016
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Vincent Dumoulin, Jonathon Shlens, and Manjunath Kudlur · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2016
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Pruning convolutional neural networks for resource efficient inference
Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, and Jan Kautz · 2016
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Runtime configurable deep neural networks for energy-accuracy trade-off
Hokchhay Tann, Soheil Hashemi, R Bahar, and Sherief Reda · 2016
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Learning structured sparsity in deep neural networks
Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li · 2016
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Towards effective low-bitwidth convolutional neural networks
Bohan Zhuang, Chunhua Shen, Mingkui Tan, Lingqiao Liu, and Ian Reid · 2016
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Structured pruning of deep convolutional neural networks
Sajid Anwar, Kyuyeon Hwang, and Wonyong Sung · 2017
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Channel pruning for accelerating very deep neural networks
Yihui He, Xiangyu Zhang, and Jian Sun · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Anytime neural networks via joint optimization of auxiliary losses
Skipnet: Learning dynamic routing in convolutional networks
Xin Wang, Fisher Yu, Zi-Yi Dou, and Joseph E Gonzalez · 2017
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Blockdrop: Dynamic inference paths in residual networks
Zuxuan Wu, Tushar Nagarajan, Abhishek Kumar, Steven Rennie, Larry S Davis, Kristen Grauman, and Rogerio Feris · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Shufflenet: An extremely efficient convolutional neural network for mobile devices
Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, and Jian Sun · 2017
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mmdetection
Kai Chen, Jiangmiao Pang, Jiaqi Wang, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jianping Shi, Wanli Ouyang, Chen Change Loy, and Dahua Lin · 2018
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Hanzhang Hu, Debadeepta Dey, J Andrew Bagnell, and Martial Hebert · 2017
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Multi-scale dense networks for resource efficient image classification
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, and Kilian Q Weinberger · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge J Belongie · 2017
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Learning nested sparse structures in deep neural networks
Eunwoo Kim, Chanho Ahn, and Songhwai Oh · 2017
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Runtime neural pruning
Ji Lin, Yongming Rao, Jiwen Lu, and Jie Zhou · 2017
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Dynamic deep neural networks: Optimizing accuracy-efficiency trade-offs by selective execution
Lanlan Liu and Jia Deng · 2017
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Learning efficient convolutional networks through network slimming
Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, and Changshui Zhang · 2017
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Feature-wise transformations
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Detectron
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Ai benchmark: Running deep neural networks on android smartphones
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Stochastic downsampling for cost-adjustable inference and improved regularization in convolutional networks
Jason Kuen, Xiangfei Kong, Zhe Lin, Gang Wang, Jianxiong Yin, Simon See, and Yap-Peng Tan · 2018
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Efficient video object segmentation via network modulation
Linjie Yang, Yanran Wang, Xuehan Xiong, Jianchao Yang, and Aggelos K Katsaggelos · 2018
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Rethinking the smaller-norm-less-informative assumption in channel pruning of convolution layers
Jianbo Ye, Xin Lu, Zhe Lin, and James Z Wang · 2018
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