Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

@article{Girshick2014RichFH,
  title={Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation},
  author={Ross B. Girshick and Jeff Donahue and Trevor Darrell and Jitendra Malik},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2014},
  pages={580-587}
}
Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that typically combine multiple low-level image features with high-level context. In this paper, we propose a simple and scalable detection algorithm that improves mean average precision (mAP) by more than 30% relative to the previous best result on VOC 2012 -- achieving a mAP of 53.3%. Our approach combines two key insights… CONTINUE READING
Highly Influential
This paper has highly influenced 794 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 7,568 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 35 times over the past 90 days. VIEW TWEETS

Topics

Statistics

0100020002012201320142015201620172018
Citations per Year

7,568 Citations

Semantic Scholar estimates that this publication has 7,568 citations based on the available data.

See our FAQ for additional information.

Blog posts, news articles and tweet counts and IDs sourced by
Altmetric.com