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CLIPTraVeLGAN for Semantically Robust Unpaired Image Translation

EasyChair Preprint 9933

12 pagesDate: April 6, 2023

Abstract

In this paper a novel approach for semantically robust unpaired image translation is presented. CLIPTraVeLGAN replaces the Siamese network in TraVeLGAN with a contrastively pretrained language-image model (CLIP) with frozen weights. This approach significantly simplifies the model selection and training process of TraVeLGAN, making it more robust and easier to use.

Keyphrases: CLIP, GAN, Transfer Knowledge, image-to-image translation

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:9933,
  author    = {Yevgeniy Bodyanskiy and Nataliya Ryabova and Roman Lavrynenko},
  title     = {CLIPTraVeLGAN for Semantically Robust Unpaired Image Translation},
  howpublished = {EasyChair Preprint 9933},
  year      = {EasyChair, 2023}}
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