milenagazdieva/ExtremalNeuralOptimalTransport
PyTorch implementation of "Extremal Domain Translation with Neural Optimal Transport" (NeurIPS 2023)
This project helps image designers and researchers transform images from one style or domain to another, like turning a photo of a handbag into a shoe, or a real face into a comic face. You provide two sets of images representing different styles or domains, and it generates new images that translate the content of the first set into the style of the second. This tool is for anyone working with unpaired image-to-image translation, such as digital artists, game developers, or researchers exploring generative models.
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Use this if you need to translate images between two different domains while having fine-grained control over how similar the translated image is to the original source.
Not ideal if you need a simple, off-the-shelf solution for paired image-to-image translation or if your primary goal is maximum image diversity without similarity control.
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Jupyter Notebook
License
MIT
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Last pushed
Dec 24, 2024
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