Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

@article{He2015SpatialPP,
  title={Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition},
  author={Kaiming He and X. Zhang and Shaoqing Ren and Jian Sun},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={37},
  pages={1904-1916}
}
  • Kaiming He, X. Zhang, +1 author Jian Sun
  • Published 2015
  • Computer Science
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224<inline-formula><tex-math>$\times$ </tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="he-ieq1-2389824.gif"/></alternatives></inline-formula>224) input image. [...] Key Method Pyramid pooling is also robust to object deformations. With these advantages, SPP-net should in general improve all CNN-based image classification methods. On the ImageNet 2012 dataset, we demonstrate that SPP-net boosts the accuracy of…Expand Abstract
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