TL;DR
This paper provides a comprehensive review of imbalance issues in object detection, introducing a taxonomy, analyzing existing solutions, and highlighting open challenges to guide future research.
Contribution
It offers a systematic taxonomy of imbalance problems in object detection and critically reviews current solutions and open issues in the field.
Findings
Identification of major imbalance problems in object detection
Critical analysis of existing solutions
Highlighting of unresolved open issues
Abstract
In this paper, we present a comprehensive review of the imbalance problems in object detection. To analyze the problems in a systematic manner, we introduce a problem-based taxonomy. Following this taxonomy, we discuss each problem in depth and present a unifying yet critical perspective on the solutions in the literature. In addition, we identify major open issues regarding the existing imbalance problems as well as imbalance problems that have not been discussed before. Moreover, in order to keep our review up to date, we provide an accompanying webpage which catalogs papers addressing imbalance problems, according to our problem-based taxonomy. Researchers can track newer studies on this webpage available at: https://github.com/kemaloksuz/ObjectDetectionImbalance .
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