Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (5): 10-24.doi: 10.11896/jsjkx.210200038

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Survey Progress on Image Instance Segmentation Methods of Deep Convolutional Neural Network

HU Fu-yuan1,2, WAN Xin-jun1,3, SHEN Ming-fei1, XU Jiang-lang1,3, YAO Rui4, TAO Zhong-ben1,2   

  1. 1 School of Electronic & Information Engineering,Suzhou University of Science and Technology,Suzhou,Jiangsu 215009,China
    2 Virtual Reality Key Laboratory of Intelligent Interaction and Application Technology of Suzhou,Suzhou University of Science and Technology,Suzhou,Jiangsu 215009,China
    3 Suzhou Key Laboratory for Big Data and Information Service,Suzhou University of Science and Technology,Suzhou,Jiangsu 215009,China
    4 School of Computer Science and Technology,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China
  • Received:2021-02-03 Revised:2021-07-09 Online:2022-05-15 Published:2022-05-06
  • About author:HU Fu-yuan,born in 1978,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include machine learning and computer vision.
    WAN Xin-jun,born in 1996,postgra-duate,is a member of China Computer Federation.His main research interests include deep learning and computer vision.
  • Supported by:
    National Natural Science Foundation of China(61876121,61801323),Primary Research & Development Plan of Jiangsu Province(BE2017663) and Foundation of Natural Science Research Program in Jiangsu Province Higher Education(19KJB520054,19KJB110021,20KJB520018).

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Abstract: Image instance segmentation is an important part of image processing and computer vision technology about image understanding.With the development of deep learning and deep convolutional neural network,image instance segmentation method based on deep convolutional neural network has made great progress.Instance segmentation task is actually the combination of target detection and semantic segmentation,which can complete the task of recognizing the target contour in the image at thepixel level.Instance segmentation can not only locate the position of the object in the image,segment all the objects from the pixel level,but also mark different individuals of the same category in the image,which is not only the pixel level segmentation of the image,but also the instance level understanding.Firstly,the reason of image segmentation and the function of deep convolution neural network are described.Then,according to the process and characteristics of image instance segmentation methods,the research progress of image instance segmentation is introduced from two-stage and single-stage perspectives,and the advantages and disadvantages of the two methods are described in detail.Then,the design ideas of region,feature extraction and mask are summarized.In addition,the performance evaluation criteria and common public data sets of image instance segmentation methods are summarized,and on this basis,the segmentation accuracy of mainstream image instance segmentation models is compared and evaluated.Finally,it points out the problems and solutions of the current image instance segmentation,summarizes the development of image instance segmentation and prospects for the future.

Key words: Deep convolutional neural network, Instance segmentation, Object detection, Semantic segmentation, Single stage, Two stage

CLC Number: 

  • TP391.4
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