An efficient implementation of GPNN

Last update: Apr 16, 2022

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Overview

Efficient-GPNN

An efficient implementation of GPNN as depicted in "Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models"

This is the version of GPNN I used to compare with my model in the reaserach done for writing the paper "Generating natural images with direct patch distributions matching [CVPR 2022]"

While writing this implementation I consulted the implementaion in https://github.com/iyttor/GPNN.git. My implementation offers more simplicity, a faster pytorch computiion of the NN matrix and and a low memory version of the computation done in O(N+M) as suggested in the suplementary of the paper: https://www.wisdom.weizmann.ac.il/~vision/gpnn/

Image reshuffling

# python3 scripts/reshuffle.py

Image Retargeting

# python3 scripts/retarget.py

Image style transfer

# python3 scripts/style_transfer.py

Owner

I'm an M.S.c student at the Hebrew University of Jerusalem. My current research deals with Generative Modeling of vision data

GitHub Repository

This repository contains the code and models for the following paper.

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