A Brief Comparison of Deep Learning Methods for Semantic Segmentation

Abstract

Semantic segmentation is widely used in many fields, which is the key and difficult point in computer vision field.In recent years, with the rapid development of deep learning, deep learning has greatly improved the performance of semantic segmentation. Many methods have been proposed.This paper mainly reviews the research progress of semantic segmentation model based on convolutional neural network (CNN), compares the methods of the same class, and analyzes the connection and difference of each method. In this paper, we mainly discuss the recent semantic segmentation models to improve segmentation accuracy from different strategies, and compare and analyze the relationships and differences between these methods. we also prospected the future development direction of semantic segmentation methods.This paper hopes to give readers an understanding of the progress and challenges of CNN based semantic segmentation research.