activity
20182024
most citedImage Resizing by Reconstruction from Deep Features

5 citations · 10 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2024

Masked Extended Attention for Zero-Shot Virtual Try-On In The Wild

Nadav Orzech, Yotam Nitzan, Ulysse Mizrahi +2

Virtual Try-On (VTON) is a highly active line of research, with increasing demand. It aims to replace a piece of garment in an image with one from another, while preserving person…

cs.CV2021

Leveraging in-domain supervision for unsupervised image-to-image translation tasks via multi-stream generators

Dvir Yerushalmi, Dov Danon, Amit H. Bermano

Supervision for image-to-image translation (I2I) tasks is hard to come by, but bears significant effect on the resulting quality. In this paper, we observe that for many Unsupervis…

cs.CV2020★ 3 cited

BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal Transfer

Or Patashnik, Dov Danon, Hao Zhang +1

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. We introduce a new unsupe…

cs.CV2020

Single Pair Cross-Modality Super Resolution

Guy Shacht, Sharon Fogel, Dov Danon +2

Non-visual imaging sensors are widely used in the industry for different purposes. Those sensors are more expensive than visual (RGB) sensors, and usually produce images with lower…

cs.CV2020★ 1 cited

Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation

Moab Arar, Yiftach Ginger, Dov Danon +3

Many applications, such as autonomous driving, heavily rely on multi-modal data where spatial alignment between the modalities is required. Most multi-modal registration methods st…

eess.IV2019

Solving Jigsaw Puzzles with Eroded Boundaries

Dov Bridger, Dov Danon, Ayellet Tal

Jigsaw puzzle solving is an intriguing problem which has been explored in computer vision for decades. This paper focuses on a specific variant of the problem - solving puzzles wit…