preprintarXiv (Cornell University)Apr 17, 2023GREEN OA

DETRs Beat YOLOs on Real-time Object Detection

ZYZhao, YianLWLv, WenyuSXShangliang XuJWJinman WeiGWGuanzhong Wang
Indexed inarxivdatacite

Abstract

The YOLO series has become the most popular framework for real-time object detection due to its reasonable trade-off between speed and accuracy. However, we observe that the speed and accuracy of YOLOs are negatively affected by the NMS. Recently, end-to-end Transformer-based detectors (DETRs) have provided an alternative to eliminating NMS. Nevertheless, the high computational cost limits their practicality and hinders them from fully exploiting the advantage of excluding NMS. In this paper, we propose the Real-Time DEtection TRansformer (RT-DETR), the first real-time end-to-end object detector to our best knowledge that addresses the above dilemma. We build RT-DETR in two steps, drawing on the advanced DETR:…

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Authors

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Topics & keywords

Keywords
  • Computer science
  • Encoder
  • Detector
  • Real-time computing
  • Object detection
  • Data mining
  • Speedup
  • Artificial intelligence
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