Object Detection in 20 Years: A Survey
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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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The record
- Venue
- Proceedings of the IEEE
- Topic
- Advanced Neural Network Applications
- Field
- Computer Science
- Canadian institutions
- Carleton University
- Funders
- Fundamental Research Funds for the Central UniversitiesNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
- Keywords
- Computer scienceObject (grammar)Artificial intelligenceComputer vision
- Has abstract in OpenAlex
- yes