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MINI REVIEW article

Front. Signal Process.
Sec. Image Processing
Volume 4 - 2024 | doi: 10.3389/frsip.2024.1356793

Salient Object Detection:A Mini Review Provisionally Accepted

Xiuwenxin Wang1 Siyue Yu1 ENG GEE LIM1* M. L. Dennis Wong2*
  • 1Xi'an Jiaotong-Liverpool University, China
  • 2Newcastle University, United Kingdom

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This paper presents a mini-review of recent works in Salient Object Detection (SOD). First, We introduce SOD and its application in image processing tasks and applications. Following this, we discuss the conventional methods for SOD and present several recent works in this category. With the start of deep learning AI algorithms, SOD has also benefited from deep learning. Here, we present and discuss Deep learning-based SOD according to its training mechanism, i.e. fully supervised and weakly supervised. For the benefit of the readers, we have also included some standard data sets assembled for SOD research.

Keywords: Computer Vision, Salient object detection, Conventional Salient Object Detection, deep learning, Mini review

Received: 16 Dec 2023; Accepted: 22 Apr 2024.

Copyright: © 2024 Wang, Yu, LIM and Wong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Prof. ENG GEE LIM, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, Jiangsu Province, China
Mx. M. L. Dennis Wong, Newcastle University, Newcastle upon Tyne, NE1 7RU, North East England, United Kingdom