Semantic Segmentation记录(个人)
来源:互联网 发布:软件服务收费模式 编辑:程序博客网 时间:2024/06/05 02:54
Under construction!
Semantic Segmentation论文列表
Deep Learning Methods
FCN
[Paper] Learning a Deep Convolutional Network for Image Super-Resolution
[Year] CVPR 2015
[Authors] Evan Shelhamer, Jonathan Long, Trevor Darrell
[Pages]
https://github.com/shelhamer/fcn.berkeleyvision.org (official)
https://github.com/MarvinTeichmann/tensorflow-fcn (tensorflow)
https://github.com/wkentaro/pytorch-fcn (pytorch)
[Description]
1) 首篇(?)使用end-to-end CNN实现Semantic Segmentation,文中提到FCN与提取patch逐像素分类是等价的,但FCN中相邻patch间可以共享计算,因此大大提高了效率
2) 把全连接视为一种卷积
3) 特征图通过deconvolution(初始为bilinear interpolation)上采样,恢复为原来的分辨率
4) 使用skip connection改善coarse segmentation mapsnull
[Paper] From Image-level to Pixel-level Labeling with Convolutional Networks
[Year] CVPR 2015
[Authors] Pedro O. Pinheiro, Ronan Collobert
[Pages]
[Description]zoom-out
[Paper] Feedforward semantic segmentation with zoom-out features
[Year] CVPR 2015
[Authors] Mohammadreza Mostajabi, Payman Yadollahpour, Gregory Shakhnarovich
[Pages] https://bitbucket.org/m_mostajabi/zoom-out-release
[Description]DeepLab
[Paper] Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
[Year] ICLR 2015
[Authors] Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille
[Pages] https://bitbucket.org/deeplab/deeplab-public[Paper] Weakly- and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation
[Year] ICCV 2015
[Authors] George Papandreou, Liang-Chieh Chen, Kevin Murphy, Alan L. YuilleDeepLab-V2
[Paper] DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
[Year] arXiv 2016
[Authors] Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille
[Pages]
http://liangchiehchen.com/projects/DeepLab.html
https://github.com/DrSleep/tensorflow-deeplab-resnet (tensorflow)
https://github.com/isht7/pytorch-deeplab-resnet (pytorch)DeepLab-V3
[Paper] Rethinking Atrous Convolution for Semantic Image Segmentation
[Year] arXiv 2017
[Authors] Liang-Chieh Chen, George Papandreou, Florian Schroff, Hartwig Adam
[Pages]CRFasRNN
[Paper] Conditional Random Fields as Recurrent Neural Networks
[Year] ICCV 2015
[Authors] Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr
[Pages] http://www.robots.ox.ac.uk/~szheng/CRFasRNN.html
[Description]DeconvNet
[Paper] Learning Deconvolution Network for Semantic Segmentation
[Year] ICCV 2015
[Authors] Hyeonwoo Noh, Seunghoon Hong, Bohyung Han
[Pages]
http://cvlab.postech.ac.kr/research/deconvnet/
https://github.com/fabianbormann/Tensorflow-DeconvNet-Segmentation (tensorflow)
[Description]SegNet
[Paper] SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling
[Year] arXiv 2015
[Authors] Alex Kendall, Vijay Badrinarayanan, Roberto Cipolla
[Pages] http://mi.eng.cam.ac.uk/projects/segnet/
[Description][Paper] SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
[Year] PAMI 2017
[Authors] Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla
[Description]DeconvNet
[Paper] Learning Deconvolution Network for Semantic Segmentation
[Year] ICCV 2015
[Authors] Hyeonwoo Noh, Seunghoon Hong, Bohyung Han
[Pages]
http://cvlab.postech.ac.kr/research/deconvnet/
https://github.com/fabianbormann/Tensorflow-DeconvNet-Segmentation (tensorflow)
[Description]BoxSup
[Paper] BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
[Year] arXiv 2015
[Authors]
[Pages]
[Description][Paper] Efficient piecewise training of deep structured models for semantic segmentation
[Year] CVPR 2016
[Authors]
[Pages]
[Description]ParseNet
[Paper] ParseNet: Looking Wider to See Better
[Year] ICLR 2016
[Authors] Wei Liu, Andrew Rabinovich, Alexander C. Berg
[Pages] https://github.com/weiliu89/caffe/tree/fcn
[Description]
Datasets
voc2012
MSCOCO
sources & lists
https://handong1587.github.io/deep_learning/2015/10/09/segmentation.html
https://github.com/mrgloom/awesome-semantic-segmentation