no code implementations • 30 Dec 2021 • Dvir Yerushalmi, Dov Danon, Amit H. Bermano
In addition, we propose training a semantic segmentation network along with the translation task, and to leverage this output as a loss term that improves robustness.
1 code implementation • 5 Oct 2020 • Or Patashnik, Dov Danon, Hao Zhang, Daniel Cohen-Or
State-of-the-art image-to-image translation methods tend to struggle in an imbalanced domain setting, where one image domain lacks richness and diversity.
no code implementations • CVPR 2021 • Guy Shacht, Sharon Fogel, Dov Danon, Daniel Cohen-Or, Ilya Leizerson
The network is trained on the two input images only, learns their internal statistics and correlations, and applies them to up-sample the target modality.
1 code implementation • CVPR 2020 • Moab Arar, Yiftach Ginger, Dov Danon, Ilya Leizerson, Amit Bermano, Daniel Cohen-Or
In this work, we bypass the difficulties of developing cross-modality similarity measures, by training an image-to-image translation network on the two input modalities.
no code implementations • 17 Apr 2019 • Moab Arar, Dov Danon, Daniel Cohen-Or, Ariel Shamir
In this paper we perform image resizing in feature space where the deep layers of a neural network contain rich important semantic information.
no code implementations • 15 Apr 2019 • Yiftach Ginger, Dov Danon, Hadar Averbuch-Elor, Daniel Cohen-Or
As a result, in recent years more attention has been given to techniques that learn the mapping from unpaired sets.