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1. arxiv.org › abs › 1506[1506.01497] Faster R-CNN: Towards Real-Time Object Detection ...

   arxiv.org › abs › 1506

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   Jun 4, 2015 · Faster R-CNN is a convolutional network that combines region proposal and detection networks to achieve fast and accurate object detection. The paper presents the method, experiments, and code of Faster R-CNN, and shows its performance on PASCAL VOC and COCO datasets.

   • Author: Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

   • Publish Year: 2015

2. Videos

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     Faster R-CNN Explanation | Region Proposal Network

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     R-CNN, Fast R-CNN and Faster R-CNN explained

     22 Nov 2021

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     12:48

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     1 Object Detection Using Faster R-CNN

     9 Nov 2020

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3. towardsdatascience.com › understanding-andUnderstanding and Implementing Faster R-CNN: A Step-By-Step Guide

   towardsdatascience.com › understanding-and

   Nov 2, 2022 · The Faster R-CNN model takes the following approach: The Image first passes through the backbone network to get an output feature map, and the ground truth bounding boxes of the image get projected onto the feature map. The backbone network is usually a dense convolutional network like ResNet or VGG16.

   • Author: Neeraj Krishna

4. github.com › trzy › FasterRCNNFaster R-CNN in PyTorch and TensorFlow 2 w/ Keras - GitHub

   github.com › trzy › FasterRCNN

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   A fresh implementation of the Faster R-CNN object detection model using Python 3.7 and Keras. The code replicates the original paper's results and includes VGG-16 and ResNet backbones.

5. ieeexplore.ieee.org › document › 7485869Faster R-CNN: Towards Real-Time Object Detection with Region ...

   ieeexplore.ieee.org › document › 7485869

   Jun 6, 2016 · Learn how to use a Region Proposal Network (RPN) to generate high-quality region proposals for Fast R-CNN, a state-of-the-art object detection network. The paper presents the architecture, training, and evaluation of Faster R-CNN, and its applications on PASCAL VOC and MS COCO datasets.

   • Author: Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

   • Publish Year: 2017

6. paperswithcode.com › method › faster-r-cnnFaster R-CNN Explained - Papers With Code

   paperswithcode.com › method › faster-r-cnn

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   Faster R-CNN is a convolutional network that combines region proposal network (RPN) and Fast R-CNN for object detection. Learn how it works, see papers and code, and compare with other models.

7. towardsdatascience.com › faster-r-cnn-for-objectFaster R-CNN for object detection | by Shilpa Ananth ...

   towardsdatascience.com › faster-r-cnn-for-object

   Aug 9, 2019 · The most widely used state of the art version of the R-CNN family — Faster R-CNN was first published in 2015. This article, the third and final one of a series to understand the fundamentals of current day object detection elaborates the technical details of the Faster R-CNN detection pipeline.

8. People also ask

   What is fast R-CNN?

   • In the rest of the article, “Faster R-CNN” usually refers to a detection pipeline that uses the RPN as a region proposal algorithm, and Fast R-CNN as a detector network. The region proposal network (RPN) starts with the input image being fed into the backbone convolutional neural network.

   Faster R-CNN for object detection - Towards Data Science

   towardsdatascience.com/faster-r-cnn-for-object-detection-a-technical-summary-474c5b857b46

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   What is faster R-CNN architecture?

   • The Faster R-CNN architecture consists of the RPN as a region proposal algorithm and the Fast R-CNN as a detector network. The Fast R-CNN detector also consists of a CNN backbone, an ROI pooling layer and fully connected layers followed by two sibling branches for classification and bounding box regression as shown in Figure 3.

   Faster R-CNN for object detection - Towards Data Science

   towardsdatascience.com/faster-r-cnn-for-object-detection-a-technical-summary-474c5b857b46

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   What is a faster R-CNN model?

   • The Faster R-CNN model takes the following approach: The Image first passes through the backbone network to get an output feature map, and the ground truth bounding boxes of the image get projected onto the feature map. The backbone network is usually a dense convolutional network like ResNet or VGG16.

   Understanding and Implementing Faster R-CNN: A Step-By-Step Guide

   towardsdatascience.com/understanding-and-implementing-faster-r-cnn-a-step-by-step-guide-11acfff216b0

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   What is RPn & faster R-CNN?

   • Since then, the frameworks of RPN and Faster R-CNN have been adopted and gen-eralized to other methods, such as 3D object detection , part-based detection , instance segmentation , and image captioning . Our fast and effective object detection system has also been built in com- 1.

   Faster R-CNN: Towards Real-Time Object Detection with Region Propo…

   arxiv.org/pdf/1506.01497

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9. arxiv.org › pdf › 1506Faster R-CNN: Towards Real-Time Object Detection with Region ...

   arxiv.org › pdf › 1506

   This paper introduces a novel method for generating region proposals using a convolutional neural network that shares features with the detection network. The method achieves state-of-the-art accuracy and speed on PASCAL VOC and COCO datasets, and is the basis of the 1st-place winning entries in several ILSVRC and COCO competitions.