  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.
