Image semantic segmentation not only predicts different categories in an image

but also orientates different semantic categories locations

which has important research significance and application value. This paper expounds the latest research results and methods of image semantic segmentation

and from three perspectives: based candidate region models、based full convolutional network models and based weakly-supervised learning models. The image semantic segmentation model methods and structure based on deep convolutional neural network are deeply overviewed in this paper. This paper compares the performance of some representative semantic segmentation algorithms on the PASCAL VOC 2012 dataset.