Spatial Pyramid Pooling
Spatial Pyramid Pooling
** 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.
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
https://paperswithcode.com/paper/spatial-pyramid-pooling-in-deep-convolutional
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition