参考 https://github.com/tensorflow/models/tree/master/research/slim

使用TensorFlow-Slim进行图像分类

Rethinking Atrous Convolution for Semantic Image Segmentation
Paper: https://arxiv.org/abs/1706.05587

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Paper: https://arxiv.org/abs/1606.02147
Code: https://github.com/e-lab/ENet-training

ICNet for Real-Time Semantic Segmentation on High-Resolution Images
Paper: https://arxiv.org/abs/1704.08545
Code: https://github.com/hszhao/ICNet

(CVPR 2017) Simple Does It: Weakly Supervised Instance and Semantic Segmentation
Paper: https://arxiv.org/abs/1603.07485
Project Page: https://www.mpi-inf.mpg.de/departments/computer-vision-and-multimodal-computing/research/weakly-supervised-learning/simple-does-it-weakly-supervised-instance-and-semantic-segmentation/

Towards Real World Human Parsing: Multiple-Human Parsing in the Wild
Paper: https://arxiv.org/pdf/1705.07206.pdf

(ICCV 2015) Weakly- and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation
Paper: http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Papandreou_Weakly-_and_Semi-Supervised_ICCV_2015_paper.pdf
Project Page: http://liangchiehchen.com/projects/DeepLab_Models.html
Code: https://bitbucket.org/deeplab/deeplab-public/

(ICCV 2015) BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
Paper: http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Dai_BoxSup_Exploiting_Bounding_ICCV_2015_paper.pdf

(ICCV 2015) Human Parsing with Contextualized Convolutional Neural Network
(T-PAMI 2016) Human Parsing with Contextualized Convolutional Neural Network
Paper: http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Liang_Human_Parsing_With_ICCV_2015_paper.pdf
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7423822&queryText=human%20parsing%20with%20contextualized&newsearch=true
Project: http://hcp.sysu.edu.cn/deep-human-parsing/

(CVPR 2017) Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing
Paper: http://www.linliang.net/files/CVPR17_LIP.pdf
Project: http://hcp.sysu.edu.cn/lip/index.php
Code: https://github.com/Engineering-Course/LIP_SSL