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 .
@article{arxiv.1909.00169,
title = {Imbalance Problems in Object Detection: A Review},
author = {Kemal Oksuz and Baris Can Cam and Sinan Kalkan and Emre Akbas},
journal= {arXiv preprint arXiv:1909.00169},
year = {2020}
}