This is a PyTorch implementation of Spatial Transformer Networks by Max Jaderberg, Karen Simonyan, Andrew Zisserman and Koray Kavukcuoglu. Spatial Transformer ...
Spatial transformer networks (STN for short) allow a neural network to learn how to perform spatial transformations on the input image in order to enhance the ...
17.06.2020 · Spatial Transformer Networks in Pytorch. This repository contains a PyTorch implementation of Spatial Transformer Networks by Jaderberg et al. The results are reported on the CIFAR-10 dataset and SVHN results will be coming up shortly. Training your own model Training is made to be very simple.
Spatial transformer networks (STN for short) allow a neural network to learn how to perform spatial transformations on the input image in order to enhance the ...
Pytorch spatial transformer network with mask (STNM). STNM was used in our ICLR 2017 paper "LR-GAN: Layered Recursive Generative Adversarial Networks for ...
STN is the spatial transformer module, it takes a B*H*W*D tensor and a B*H*W*2 grid normalized to [-1,1] as an input and do bilinear sampling. AffineGridGen ...
17.06.2017 · PyTorch version of spatial transformer network Ported from https://github.com/qassemoquab/stnbhwd according to pytorch tutorial. Now support CPU and GPU. To use the ffi you need to install the cffi package from pip. Build and test