计算机科学

计算机科学 ›› 2023, Vol. 50 ›› Issue (12): 130-147.doi: 10.11896/jsjkx.221100076

• 计算机图形学&多媒体 • 上一篇    下一篇

Transformer在计算机视觉场景下的研究综述

陈洛轩1,2, 林成创3, 郑招良1,2, 莫泽枫1,2, 黄心怡1,2, 赵淦森1,2   

  1. 1 华南师范大学计算机学院 广州 510663
    2 广州市云计算安全与测评技术重点实验室 广州 510663
    3 广东省电信规划设计院有限公司 广州 510630
  • 收稿日期:2022-11-09 修回日期:2023-02-25 出版日期:2023-12-15 发布日期:2023-12-07
  • 通讯作者: 赵淦森(gzhao@m.scnu.edu.cn)
  • 作者简介:(chenlx@m.scnu.edu.cn)
  • 基金资助:
    国家自然科学基金(82271267);国家社会科学基金重大项目(19ZDA041)

Review of Transformer in Computer Vision

CHEN Luoxuan1,2, LIN Chengchuang3, ZHENG Zhaoliang1,2, MO Zefeng1,2, HUANG Xinyi1,2, ZHAO Gansen1,2   

  1. 1 School of Computer Science,South China Normal University,Guangzhou 510663,China
    2 Guangzhou Key Lab on Cloud Computing Security and Assessment Technology,Guangzhou 510663,China
    3 Guangdong Planning and Designing Institute of Telecommunications Co.,Ltd,Guangzhou 510630,China
  • Received:2022-11-09 Revised:2023-02-25 Online:2023-12-15 Published:2023-12-07
  • About author:CHEN Luoxuan,born in 1998,postgra-duate,is a member of China Computer Federation.Her main research interests include computer vision and medical image segmentation.
    ZHAO Gansen,born in 1977,Ph.D,professor.His main research interests include medical artificial intelligence,medical image,and medical data analysis.
  • Supported by:
    National Natural Science Foundation of China(82271267) and National Social Science Fund of China(19ZDA041).

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摘要： Transformer是一种基于注意力的编码器-解码器架构,其凭借长距离建模能力与并行计算能力在自然语言处理领域取得了重大突破,并逐步拓展应用至计算机视觉领域,成为了计算机视觉任务的重要研究方向。文中重点回顾与总结了Transformer在图像分类、目标检测与图像分割三大计算机视觉任务中的应用和改进。首先,以图像分类任务为切入点,从数据规模、结构特点、计算效率等方面深入分析了当前视觉Transformer存在的关键问题,并基于关键问题对解决方法和思路进行了分类。其次,全面梳理了视觉Transformer在目标检测与图像分割两大领域的研究进展,并根据结构特点、设计动机来组织这些方法,分析对比代表性方法的优点与不足。最后,对Transformer在计算机视觉任务中亟待解决的问题以及发展趋势进行了总结和探讨。

关键词: 视觉Transformer, 计算机视觉, 图像分类, 目标检测, 图像分割

Abstract: Transformer is an attention-based encoder-decoder architecture.Due to its long-range sequence modeling and parallel computing capability,Transformer have made a significant breakthrough in natural language processing and is gradually expanding to computer vision(CV) fields,which has become an important research direction in CV tasks.Three sorts of visual Transformer-based CV task,including classification,object detection and segmentation,are focused on by this paper,which summarizes their application and modification.Starting from image classification,this paper first analyses the existing issue in vision Transformer including data size,structure and computational efficiency,then sorts out the corresponding solutions according to the issue.Besides,this paper provides a literature review on object detection and segmentation,which organizes these methods accor-ding to their structures and motivations and summarizes their corresponding pros and cons.Finally,the challenges and future development trends of the Transformer in vision transformer are summarized and discussed in this paper.

Key words: Vison Transformer, Computer vision, Image classification, Object detection, Image segmentation

中图分类号: 

  • TP391
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