Conditional Random Fields as Recurrent Neural Networks

Articles citing Conditional Random Fields as Recurrent Neural Networks

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
Semantic image segmentation with deep convolutional nets and fully connected crfs LC Chen, G Papandreou, I Kokkinos, K Murphy, AL Yuille arXiv preprint arXiv:1412.7062	2014
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
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
Region-based convolutional networks for accurate object detection and segmentation R Girshick, J Donahue, T Darrell, J Malik IEEE transactions on pattern analysis and machine intelligence 38 (1), 142-158	2015
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
Instance-aware semantic segmentation via multi-task network cascades J Dai, K He, J Sun Proceedings of the IEEE Conference on Computer Vision and Pattern …	2016
Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation G Papandreou, LC Chen, KP Murphy, AL Yuille Proceedings of the IEEE international conference on computer vision, 1742-1750	2015
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
Social lstm: Human trajectory prediction in crowded spaces A Alahi, K Goel, V Ramanathan, A Robicquet, L Fei-Fei, S Savarese Proceedings of the IEEE conference on computer vision and pattern …	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
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

1 - 20

Dates and citation counts are estimated and are determined automatically by a computer program.