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Found 4 papers, 4 papers with code
FunkNN: Neural Interpolation for Functional Generation
Our answer is FunkNN -- a new convolutional network which learns how to reconstruct continuous images at arbitrary coordinates and can be applied to any image dataset.
Truly shift-equivariant convolutional neural networks with adaptive polyphase upsampling
Convolutional neural networks lack shift equivariance due to the presence of downsampling layers.
Truly shift-invariant convolutional neural networks
Thanks to the use of convolution and pooling layers, convolutional neural networks were for a long time thought to be shift-invariant.
Learning Multiscale Convolutional Dictionaries for Image Reconstruction
To close the performance gap, we thus propose a multiscale convolutional dictionary structure.
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