Fast R CNN - AshokBhat/ml GitHub Wiki

About

• Fast version of R-CNN

Paper

• Title : Fast R-CNN
• Link: https://arxiv.org/abs/1504.08083
• Date: 27 Sep 2015

Abstract

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 9× faster than R-CNN, is 213× faster at test-time, and achieves a higher mAP on PASCAL VOC 2012. Compared to SPPnet, Fast R-CNN trains VGG16 3× faster, tests 10× faster, and is more accurate.

Fast R-CNN is implemented in Python and C++ (using Caffe) and is available under the open-source MIT License at https://github.com/rbgirshick/fast-rcnn

Architecture

FAQ

• What is Fast R-CNN?
• How is it different from R-CNN

See also

• [Object detection]] : [[R-CNN]] ](/AshokBhat/ml/wiki/[Fast-R-CNN) | [Faster R-CNN]] | Yolo