Transcription of Spatial Pyramid Pooling in Deep Convolutional …
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Spatial Pyramid Pooling in Deep Convolutional …
1 Spatial Pyramid Pooling in Deep ConvolutionalNetworks for visual RecognitionKaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian SunAbstract Existing deep Convolutional neural networks (CNNs) require a fixed-size ( , 224 224) input image. This require-ment is artificial and may reduce the recognition accuracy for the images or sub-images of an arbitrary size/scale. In thiswork, we equip the networks with another Pooling strategy, Spatial Pyramid Pooling , to eliminate the above requirement. Thenew network structure, called SPP-net, can generate a fixed-length representation regardless of image size/scale. Pyramidpooling is also robust to object deformations. With these advantages, SPP-net should in general improve all CNN-based imageclassification methods. On the ImageNet 2012 dataset, we demonstrate that SPP-net boosts the accuracy of a variety of CNNarchitectures despite their different designs.
1 Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun Abstract—Existing deep convolutional neural networks (CNNs) require a fixed-size …
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