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

  title={Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks},
  author={Shaoqing Ren and Kaiming He and Ross B. Girshick and J. Sun},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  • Shaoqing Ren, Kaiming He, +1 author J. Sun
  • Published 2015
  • Medicine, Computer Science
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 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.Expand Abstract
    Revisiting Faster R-CNN: A Deeper Look at Region Proposal Network
    • 5
    • Highly Influenced
    R-FCN: Object Detection via Region-based Fully Convolutional Networks
    • 2,523
    • Open Access
    R-FCN++: Towards Accurate Region-Based Fully Convolutional Networks for Object Detection
    • 14
    • Highly Influenced
    Relief R-CNN: Utilizing Convolutional Features for Fast Object Detection
    • 7
    • Highly Influenced
    • Open Access
    Rich Features and Precise Localization with Region Proposal Network for Object Detection
    • 5
    • Highly Influenced
    • Open Access
    Real-Time Object Detection With Reduced Region Proposal Network via Multi-Feature Concatenation
    • 3
    • Highly Influenced


    Publications referenced by this paper.
    Fast R-CNN
    • 8,721
    • Open Access
    R-CNN minus R
    • 71
    • Open Access
    Scalable Object Detection Using Deep Neural Networks
    • 764
    • Open Access
    Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
    • 11,328
    • Open Access
    Object Detection Networks on Convolutional Feature Maps
    • 230
    • Open Access
    Convolutional feature masking for joint object and stuff segmentation
    • 326
    • Open Access
    Learning to Segment Object Candidates
    • 517
    • Open Access
    DeePM: A Deep Part-Based Model for Object Detection and Semantic Part Localization
    • 16
    • Open Access
    Instance-Aware Semantic Segmentation via Multi-task Network Cascades
    • 725
    • Open Access
    Scalable, High-Quality Object Detection
    • 265
    • Open Access