Abstract

Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Over the past two decades, we have seen a rapid technological evolution of object detection and its profound impact on the entire computer vision field. If we consider today's object detection technique as a revolution driven by deep learning, then, back in the 1990s, we would see the ingenious thinking and long-term perspective design of early computer vision. This article extensively reviews this fast-moving research field in the light of technical evolution, spanning over a quarter-century's time (from the 1990s to 2022). A number of topics have been covered in this article, including the milestone detectors in history, detection datasets, metrics, fundamental building blocks of the detection system, speedup techniques, and recent state-of-the-art detection methods.

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Computer scienceObject (grammar)Artificial intelligenceComputer vision

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Publication Info

Year
2023
Type
article
Volume
111
Issue
3
Pages
257-276
Citations
2427
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Closed

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Cite This

Zhengxia Zou, Keyan Chen, Zhenwei Shi et al. (2023). Object Detection in 20 Years: A Survey. Proceedings of the IEEE , 111 (3) , 257-276. https://doi.org/10.1109/jproc.2023.3238524

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DOI
10.1109/jproc.2023.3238524