Oksuz Kemal, Cam Baris Can, Kalkan Sinan, Akbas Emre
IEEE Trans Pattern Anal Mach Intell. 2021 Oct;43(10):3388-3415. doi: 10.1109/TPAMI.2020.2981890. Epub 2021 Sep 2.
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.
在本文中,我们对目标检测中的不平衡问题进行了全面综述。为了系统地分析这些问题,我们引入了一种基于问题的分类法。按照这种分类法,我们深入讨论了每个问题,并对文献中的解决方案提出了一个统一而关键的观点。此外,我们还确定了关于现有不平衡问题以及此前未被讨论过的不平衡问题的主要开放性问题。而且,为了使我们的综述与时俱进,我们提供了一个配套网页,该网页根据我们基于问题的分类法对解决不平衡问题的论文进行了编目。研究人员可以在这个网页上追踪最新的研究,网址为:https://github.com/kemaloksuz/ObjectDetectionImbalance 。