no code implementations • 18 Dec 2023 • Ahmet Burak Yildirim, Hamza Pehlivan, Aysegul Dundar
However, their results either suffer from low fidelity to the input image or poor editing qualities, especially for edits that require large transformations.
no code implementations • ICCV 2023 • Ahmet Burak Yildirim, Hamza Pehlivan, Bahri Batuhan Bilecen, Aysegul Dundar
Specifically, we propose to learn an encoder and mixing network to combine encoded features from erased images with StyleGAN's mapped features from random samples.
1 code implementation • 6 Apr 2023 • Ahmet Burak Yildirim, Vedat Baday, Erkut Erdem, Aykut Erdem, Aysegul Dundar
From the application point of view, a user needs to generate the masks for the objects they would like to remove which can be time-consuming and prone to errors.