Spatial Pyramid Pooling

2000년 도입 · 논문 285편에서 사용

Spatial Pyramid Pooling (SPP) is a pooling layer that removes the fixed-size constraint of the network, i.e. a CNN does not require a fixed-size input image. Specifically, we add an SPP layer on top of the last convolutional layer. The SPP layer pools the features and generates fixed-length outputs, which are then fed into the fully-connected layers (or other classifiers). In other words, we perform some information aggregation at a deeper stage of the network hierarchy (between convolutional layers and fully-connected layers) to avoid the need for cropping or warping at the beginning.

출처: Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

소개 논문: Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition