Multi-Scale Context Aggregation by Dilated Convolutions.

Articles citing Multi-Scale Context Aggregation by Dilated Convolutions.

Title / Author	Year
Fully convolutional networks for semantic segmentation J Long, E Shelhamer, T Darrell Proceedings of the IEEE conference on computer vision and pattern …	2015
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs LC Chen, G Papandreou, I Kokkinos, K Murphy, AL Yuille IEEE transactions on pattern analysis and machine intelligence 40 (4), 834-848	2017
Segnet: A deep convolutional encoder-decoder architecture for image segmentation V Badrinarayanan, A Kendall, R Cipolla IEEE transactions on pattern analysis and machine intelligence 39 (12), 2481 …	2017
The cityscapes dataset for semantic urban scene understanding M Cordts, M Omran, S Ramos, T Rehfeld, M Enzweiler, R Benenson, ... Proceedings of the IEEE conference on computer vision and pattern …	2016
Pyramid scene parsing network H Zhao, J Shi, X Qi, X Wang, J Jia Proceedings of the IEEE conference on computer vision and pattern …	2017
Wavenet: A generative model for raw audio A Oord, S Dieleman, H Zen, K Simonyan, O Vinyals, A Graves, ... arXiv preprint arXiv:1609.03499	2016
Rethinking atrous convolution for semantic image segmentation LC Chen, G Papandreou, F Schroff, H Adam arXiv preprint arXiv:1706.05587	2017
Refinenet: Multi-path refinement networks for high-resolution semantic segmentation G Lin, A Milan, C Shen, I Reid Proceedings of the IEEE conference on computer vision and pattern …	2017
Colorful image colorization R Zhang, P Isola, AA Efros European conference on computer vision, 649-666	2016
Deformable convolutional networks J Dai, H Qi, Y Xiong, Y Li, G Zhang, H Hu, Y Wei Proceedings of the IEEE international conference on computer vision, 764-773	2017
Recent advances in convolutional neural networks J Gu, Z Wang, J Kuen, L Ma, A Shahroudy, B Shuai, T Liu, X Wang, ... Pattern Recognition 77, 354-377	2018
What uncertainties do we need in bayesian deep learning for computer vision? A Kendall, Y Gal Advances in neural information processing systems, 5574-5584	2017
Density estimation using real nvp L Dinh, J Sohl-Dickstein, S Bengio arXiv preprint arXiv:1605.08803	2016
A guide to convolution arithmetic for deep learning V Dumoulin, F Visin arXiv preprint arXiv:1603.07285	2016
The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation S Jégou, M Drozdzal, D Vazquez, A Romero, Y Bengio Proceedings of the IEEE conference on computer vision and pattern …	2017
Enet: A deep neural network architecture for real-time semantic segmentation A Paszke, A Chaurasia, S Kim, E Culurciello arXiv preprint arXiv:1606.02147	2016
An empirical evaluation of generic convolutional and recurrent networks for sequence modeling S Bai, JZ Kolter, V Koltun arXiv preprint arXiv:1803.01271	2018
Playing for data: Ground truth from computer games SR Richter, V Vineet, S Roth, V Koltun European conference on computer vision, 102-118	2016
Globally and locally consistent image completion S Iizuka, E Simo-Serra, H Ishikawa ACM Transactions on Graphics (ToG) 36 (4), 1-14	2017
Deep convolutional neural networks for image classification: A comprehensive review W Rawat, Z Wang Neural computation 29 (9), 2352-2449	2017

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