Fast R-CNN

@article{Girshick2015FastR,
  title={Fast R-CNN},
  author={Ross B. Girshick},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={1440-1448}
}
  • Ross B. Girshick
  • Published 2015
  • Computer Science
  • 2015 IEEE International Conference on Computer Vision (ICCV)
This paper proposes a Fast Region-based Convolutional Network method (Fast R-CNN) for object detection. Fast R-CNN builds on previous work to efficiently classify object proposals using deep convolutional networks. Compared to previous work, Fast R-CNN employs several innovations to improve training and testing speed while also increasing detection accuracy. Fast R-CNN trains the very deep VGG16 network 9x faster than R-CNN, is 213x faster at test-time, and achieves a higher mAP on PASCAL VOC… Expand
View on IEEE
cs.nyu.edu
11,153 Citations
Highly Influential Citations
2,331
Background Citations
3,173
Methods Citations
5,281
Results Citations
84

11,153 Citations

Citation Type

Citation Type

Study of object detection based on Faster R-CNN
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Analysis of Object Detection Performance Based on Faster R-CNN
IE 534 Final Project : Faster R-CNN
R-FCN: Object Detection via Region-based Fully Convolutional Networks
Relief R-CNN: Utilizing Convolutional Features for Fast Object Detection
Relief R-CNN: Utilizing Convolutional Feature Interrelationship for Fast Object Detection Deployment
Refining faster-RCNN for accurate object detection
Survey on Faster Region Convolution Neural Network for Object Detection
Atrous Faster R-CNN for Small Scale Object Detection
  • Tongfan Guan, H. Zhu
  • Computer Science
  • 2017 2nd International Conference on Multimedia and Image Processing (ICMIP)
  • 2017
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 35 REFERENCES
Region-Based Convolutional Networks for Accurate Object Detection and Segmentation
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Scalable Object Detection Using Deep Neural Networks
Return of the Devil in the Details: Delving Deep into Convolutional Nets
ImageNet classification with deep convolutional neural networks
Very Deep Convolutional Networks for Large-Scale Image Recognition
segDeepM: Exploiting segmentation and context in deep neural networks for object detection
Caffe: Convolutional Architecture for Fast Feature Embedding
What Makes for Effective Detection Proposals?
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
...
1
2
3
4
...