Fully Convolutional Networks for Semantic Segmentation

Articles citing Fully Convolutional Networks for Semantic Segmentation

Title / Author	Year
Deep residual learning for image recognition K He, X Zhang, S Ren, J Sun Proceedings of the IEEE conference on computer vision and pattern …	2016
Very deep convolutional networks for large-scale image recognition K Simonyan, A Zisserman arXiv preprint arXiv:1409.1556	2014
Faster r-cnn: Towards real-time object detection with region proposal networks S Ren, K He, R Girshick, J Sun Advances in neural information processing systems, 91-99	2015
U-net: Convolutional networks for biomedical image segmentation O Ronneberger, P Fischer, T Brox International Conference on Medical image computing and computer-assisted …	2015
Densely connected convolutional networks G Huang, Z Liu, L Van Der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …	2017
Ssd: Single shot multibox detector W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg European conference on computer vision, 21-37	2016
Rethinking the inception architecture for computer vision C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna Proceedings of the IEEE conference on computer vision and pattern …	2016
Mask r-cnn K He, G Gkioxari, P Dollár, R Girshick Proceedings of the IEEE international conference on computer vision, 2961-2969	2017
Image-to-image translation with conditional adversarial networks P Isola, JY Zhu, T Zhou, AA Efros Proceedings of the IEEE conference on computer vision and pattern …	2017
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
Unpaired image-to-image translation using cycle-consistent adversarial networks JY Zhu, T Park, P Isola, AA Efros Proceedings of the IEEE international conference on computer vision, 2223-2232	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
Inception-v4, inception-resnet and the impact of residual connections on learning C Szegedy, S Ioffe, V Vanhoucke, AA Alemi Thirty-first AAAI conference on artificial intelligence	2017
Feature pyramid networks for object detection TY Lin, P Dollár, R Girshick, K He, B Hariharan, S Belongie Proceedings of the IEEE conference on computer vision and pattern …	2017
Deep contextualized word representations ME Peters, M Neumann, M Iyyer, M Gardner, C Clark, K Lee, ... arXiv preprint arXiv:1802.05365	2018
Focal loss for dense object detection TY Lin, P Goyal, R Girshick, K He, P Dollár Proceedings of the IEEE international conference on computer vision, 2980-2988	2017
A survey on deep learning in medical image analysis G Litjens, T Kooi, BE Bejnordi, AAA Setio, F Ciompi, M Ghafoorian, ... Medical image analysis 42, 60-88	2017
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
Multi-scale context aggregation by dilated convolutions F Yu, V Koltun arXiv preprint arXiv:1511.07122	2015
Squeeze-and-excitation networks J Hu, L Shen, G Sun Proceedings of the IEEE conference on computer vision and pattern …	2018

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