SPP-Net
SPP-Net
**SPP-Net** is a convolutional neural architecture that employs [spatial pyramid pooling](https://paperswithcode.com/method/spatial-pyramid-pooling) to remove the fixed-size constraint of the network. 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