Learning Deconvolution Network for Semantic Segmentation

Articles citing Learning Deconvolution Network for Semantic Segmentation

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
Multi-scale context aggregation by dilated convolutions F Yu, V Koltun arXiv preprint arXiv:1511.07122	2015
Perceptual losses for real-time style transfer and super-resolution J Johnson, A Alahi, L Fei-Fei European conference on computer vision, 694-711	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
Stacked hourglass networks for human pose estimation A Newell, K Yang, J Deng European conference on computer vision, 483-499	2016
V-net: Fully convolutional neural networks for volumetric medical image segmentation F Milletari, N Navab, SA Ahmadi 2016 Fourth International Conference on 3D Vision (3DV), 565-571	2016
Learning multi-domain convolutional neural networks for visual tracking H Nam, B Han Proceedings of the IEEE conference on computer vision and pattern …	2016
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation K Kamnitsas, C Ledig, VFJ Newcombe, JP Simpson, AD Kane, DK Menon, ... Medical image analysis 36, 61-78	2017
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
Efficient piecewise training of deep structured models for semantic segmentation G Lin, C Shen, A Van Den Hengel, I Reid Proceedings of the IEEE conference on computer vision and pattern …	2016
Deep learning for visual understanding: A review Y Guo, Y Liu, A Oerlemans, S Lao, S Wu, MS Lew Neurocomputing 187, 27-48	2016
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
Encoder-decoder with atrous separable convolution for semantic image segmentation LC Chen, Y Zhu, G Papandreou, F Schroff, H Adam Proceedings of the European conference on computer vision (ECCV), 801-818	2018
The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes G Ros, L Sellart, J Materzynska, D Vazquez, AM Lopez Proceedings of the IEEE conference on computer vision and pattern …	2016
Attention to scale: Scale-aware semantic image segmentation LC Chen, Y Yang, J Wang, W Xu, AL Yuille Proceedings of the IEEE conference on computer vision and pattern …	2016
Learning to refine object segments PO Pinheiro, TY Lin, R Collobert, P Dollár European Conference on Computer Vision, 75-91	2016
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

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