Imbalance Problems in Object Detection: A Review

Oksuz K., Cam B. C., Kalkan S., Akbas E.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, cilt.43, sa.10, ss.3388-3415, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 43 Sayı: 10
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1109/tpami.2020.2981890
  • Dergi Adı: IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, MEDLINE, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.3388-3415
  • Anahtar Kelimeler: Object detection, Taxonomy, Feature extraction, Deep learning, Pipelines, Neural networks, Pattern analysis, Object detection, imbalance, class imbalance, scale imbalance, spatial imbalance, objective imbalance, FACE DETECTION
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.