Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

@article{Ren2015FasterRT,
  title={Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks},
  author={Shaoqing Ren and Kaiming He and Ross B. Girshick and Jian Sun},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={39},
  pages={1137-1149}
}
State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. [] Key Method An RPN is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained end-to-end to generate high-quality region proposals, which are used by Fast R-CNN for detection.
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