Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Paper summary This work proposes a two stage object detection algorithm based on convolutional neural network (CNN). The first stage is region proposal, which is based on the traditional sliding window method but working on the top layer feature map of CNN (RPN). In the second stage, a fast R-CNN is applied to the proposed regions. Since the convolution layers are shared between RPN and R-CNN, and the calculation is speeded up using GPU, the algorithm can achieve near real-time (5fps).
papers.nips.cc
scholar.google.com
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, Shaoqing and He, Kaiming and Girshick, Ross B. and Sun, Jian
Neural Information Processing Systems Conference - 2015 via Bibsonomy
Keywords: dblp


Loading...
Your comment:
Loading...
Your comment:


Short Science allows researchers to publish paper summaries that are voted on and ranked!
About