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Knowledge Transfer in Vision Recognition: A Survey

  • École centrale de Lyon
  • Shanghai Jiao Tong University

Research output: Contribution to journalReview articlepeer-review

Abstract

In this survey, we propose to explore and discuss the common rules behind knowledge transfer works for vision recognition tasks. To achieve this, we firstly discuss the different kinds of reusable knowledge existing in a vision recognition task, and then we categorize different knowledge transfer approaches depending on where the knowledge comes from and where the knowledge goes. Compared to previous surveys on knowledge transfer that are from the problem-oriented perspective or from the technique-oriented perspective, our viewpoint is closer to the nature of knowledge transfer and reveals common rules behind different transfer learning settings and applications. Besides different knowledge transfer categories, we also show some research works that study the transferability between different vision recognition tasks. We further give a discussion about the introduced research works and show some potential research directions in this field.

Original languageEnglish
Article number3379344
JournalACM Computing Surveys
Volume53
Issue number2
DOIs
StatePublished - Jun 2020

Keywords

  • Knowledge transfer
  • computer vision
  • machine learning
  • transfer learning
  • vision recognition

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