Details
Paper ID 25
Medium

Categories

  • CNN
  • Fast R-CNN
  • RolPool
  • Softmax

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

Paper - https://arxiv.org/pdf/1504.08083v2.pdf

Dataset - https://cocodataset.org/#download