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cyclegannphototopainting's Introduction

Table of Contents

IMDb dataset

Rijksmuseum dataset

CycleGANN Monet2Photo results

CycleGANN Nightwatch results

CycleGANN IMDB to Rijksmuseum full painting

CycleGANN IMDB to Rijksmuseum face only (this file)

Perceived sex classification performance

Painting to Photo using CycleGann

Source: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix

Cite:

@article{zhu2017unpaired,
  title={Unpaired image-to-image translation using cycle-consistent adversarial networks},
  author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A},
  journal={arXiv preprint},
  year={2017}
}

IMDB to Rijks training

Author's implementation on the Monet2Photo model is trained with 1072 Monet painting samples and 6,287 nature photographs over 200 epochs (takes approximately 15 days with a single GPU). We have used 1234 Rijksmuseum paintings and 10,223 IMDb pictures with the same architecture. Training process took almost 18 days on Intel i5-6600 @3.30GHz equipped with NVIDIA GeForge GTX 1070 (Aero 8G OC V330 – 011R).

IMDB to Rijks trained

Faces from Rijksmuseum paintings → Painting face to photo results

Real → Fake

Real → Fake

Real → Fake

Real → Fake

Real → Fake

Real → Fake

Real → Fake

Real → Fake

Real → Fake

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