SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Articles citing SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Title / Author	Year
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
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
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size FN Iandola, S Han, MW Moskewicz, K Ashraf, WJ Dally, K Keutzer arXiv preprint arXiv:1602.07360	2016
Stacked hourglass networks for human pose estimation A Newell, K Yang, J Deng European conference on computer vision, 483-499	2016
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
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
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
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
Scene parsing through ade20k dataset B Zhou, H Zhao, X Puig, S Fidler, A Barriuso, A Torralba Proceedings of the IEEE conference on computer vision and pattern …	2017
Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding A Kendall, V Badrinarayanan, R Cipolla arXiv preprint arXiv:1511.02680	2015
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics A Kendall, Y Gal, R Cipolla Proceedings of the IEEE conference on computer vision and pattern …	2018
A review on deep learning techniques applied to semantic segmentation A Garcia-Garcia, S Orts-Escolano, S Oprea, V Villena-Martinez, ... arXiv preprint arXiv:1704.06857	2017
Understanding convolution for semantic segmentation P Wang, P Chen, Y Yuan, D Liu, Z Huang, X Hou, G Cottrell 2018 IEEE winter conference on applications of computer vision (WACV), 1451-1460	2018
Monocular 3d object detection for autonomous driving X Chen, K Kundu, Z Zhang, H Ma, S Fidler, R Urtasun Proceedings of the IEEE Conference on Computer Vision and Pattern …	2016
Semantic autoencoder for zero-shot learning E Kodirov, T Xiang, S Gong Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
End-to-end learning of geometry and context for deep stereo regression A Kendall, H Martirosyan, S Dasgupta, P Henry, R Kennedy, A Bachrach, ... Proceedings of the IEEE International Conference on Computer Vision, 66-75	2017
Icnet for real-time semantic segmentation on high-resolution images H Zhao, X Qi, X Shen, J Shi, J Jia Proceedings of the European Conference on Computer Vision (ECCV), 405-420	2018
Context encoding for semantic segmentation H Zhang, K Dana, J Shi, Z Zhang, X Wang, A Tyagi, A Agrawal Proceedings of the IEEE conference on Computer Vision and Pattern …	2018

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