Imbalance Problems in Object Detection: A Review.

Date

2020-03-19

Author

Oksuz, Kemal
Cam, Baris Can
Kalkan, Sinan
Akbaş, Emre

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Computational Theory and Mathematics, Software, Applied Mathematics, Artificial Intelligence, Computer Vision and Pattern Recognition

URI

https://hdl.handle.net/11511/70222

Journal

IEEE transactions on pattern analysis and machine intelligence

DOI

https://doi.org/10.1109/tpami.2020.2981890

Collections

Department of Computer Engineering, Article

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Citation Formats

K. Oksuz, B. C. Cam, S. Kalkan, and E. Akbaş, “Imbalance Problems in Object Detection: A Review.,” IEEE transactions on pattern analysis and machine intelligence, 2020, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/70222.