Semantic-Driven Unsupervised Image-to-Image Translation for Distinct Image Domains

Semantic-Driven Unsupervised Image-to-Image Translation for Distinct Image Domains

We expand the scope of image-to-image translation to include more distinct image domains, where the image sets have analogous structures, but may not share object types between them. Semantic-Driven Unsupervised Image-to-Image Translation for Distinct Image Domains (SUNIT) is built to more successfu...

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Bibliographic Details
Main Author: Ackerman, Wesley
Format: Others
Published: BYU ScholarsArchive 2020
Subjects:
computer science
machine learning
image-to-image translation
generative adversarial network
deep learning
unsupervised learning
convolutional neural network
Physical Sciences and Mathematics
Online Access:https://scholarsarchive.byu.edu/etd/8684
https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9684&context=etd

Internet

https://scholarsarchive.byu.edu/etd/8684
https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9684&context=etd

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