Web: http://arxiv.org/abs/2206.09210

June 23, 2022, 1:11 a.m. | Aref Abedjooy, Mehran Ebrahimi

cs.LG updates on arXiv.org arxiv.org

Deep learning techniques, especially Generative Adversarial Networks (GANs)
have significantly improved image inpainting and image-to-image translation
tasks over the past few years. To the best of our knowledge, the problem of
combining the image inpainting task with the multi-modality image-to-image
translation remains intact. In this paper, we propose a model to address this
problem. The model will be evaluated on combined night-to-day image translation
and inpainting, along with promising qualitative and quantitative results.

arxiv generative adversarial networks image inpainting networks

More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY