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Real-time semantic segmentation is of significant importance for mobile and robotics related applications.
“Adam: A method for stochastic optimization,”
Diederik Kingma and Jimmy Ba, · 2014
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“Going deeper with convolutions,”
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich, · 2015
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Song Han, Huizi Mao, and William J Dally, · 2015
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“Learning both weights and connections for efficient neural network,”
Song Han, Jeff Pool, John Tran, and William Dally, · 2015
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“Segnet: A deep convolutional encoder-decoder architecture for image segmentation,”
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla, · 2015
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“Fully convolutional networks for semantic segmentation,”
Jonathan Long, Evan Shelhamer, and Trevor Darrell, · 2015
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“U-net: Convolutional networks for biomedical image segmentation,”
Olaf Ronneberger, Philipp Fischer, and Thomas Brox, · 2015
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“Multi-scale context aggregation by dilated convolutions,”
Fisher Yu and Vladlen Koltun, · 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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“Xception: Deep learning with depthwise separable convolutions,”
François Chollet, · 2016
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“Xnor-net: Imagenet classification using binary convolutional neural networks,”
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Farhadi, · 2016
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“Quantized convolutional neural networks for mobile devices,”
Jiaxiang Wu, Cong Leng, Yuhang Wang, Qinghao Hu, and Jian Cheng, · 2016
Cited alongside, same era.
“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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“Shufflenet: An extremely efficient convolutional neural network for mobile devices,”
Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, and Jian Sun, · 2017
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“End-to-end learning of driving models from large-scale video datasets,”
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell, · 2017
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“Segicp-dsr: Dense semantic scene reconstruction and registration,”
Jay M Wong, Syler Wagner, Connor Lawson, Vincent Kee, Mitchell Hebert, Justin Rooney, Gian-Luca Mariottini, Rebecca Russell, Abraham Schneider, Rahul Chipalkatty, et al., · 2017
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“The cityscapes dataset for semantic urban scene understanding,”
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele, · 2016
Cited alongside, same era.
“Enet: A deep neural network architecture for real-time semantic segmentation,”
Adam Paszke, Abhishek Chaurasia, Sangpil Kim, and Eugenio Culurciello, · 2016
Cited alongside, same era.
Abhishek Chaurasia and Eugenio Culurciello, · 2017
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“Learning structured sparsity in deep neural networks,”
Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li, · 2082
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