Semantic-Segmentation-with-Full-Convolutional-Neural-Network

Introduction

Semantic segmentation in Weizmann horse dataset and Labeled Face in the Wild dataset.

Method

最早的全卷积语义分割网络：

https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Long_Fully_Convolutional_Networks_2015_CVPR_paper.pdf

目前比较热门的结构：

PSPNet ：Pyramid Scene Parsing Network

https://github.com/hszhao/PSPNet

DeeplabV3 ：Rethinking Atrous Convolution for Semantic Image Segmentation

https://arxiv.org/abs/1706.05587

https://github.com/NanqingD/DeepLabV3-Tensorflow

基于attention机制的：

CCNet： Criss-Cross Attention for Semantic Segmentation

https://github.com/speedinghzl/CCNet

DAN ： Dual Attention Network for Scene Segmentation

https://github.com/junfu1115/DANet

Data

The download link for Weizmann horse dataset:

http://www.msri.org/people/members/eranb/

Labeled Face in the Wild:

http://vis-www.cs.umass.edu/lfw/ http://vis-www.cs.umass.edu/lfw/part_labels/

Related semantic datasets:

https://blog.csdn.net/bevison/article/details/78123403

数据转换

python Semantic_segmentation_lfw/data_process.py

Result:

python ./imgs/ vis_result.py