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Object Detection in 20 Years: A Survey

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arxiv 1905.05055 v3 pith:T6OXBSCH submitted 2019-05-13 cs.CV

classification cs.CV
keywords detectionobjectcomputervisionevolutionfieldfundamentalrecent
verification ladder T0 review T1 audit T2 compute T3 formal

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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 paper 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 paper, including the milestone detectors in history, detection datasets, metrics, fundamental building blocks of the detection system, speed-up techniques, and the recent state-of-the-art detection methods.

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Cited by 10 Pith papers

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