activity
20172020
most citedSelf-Supervised Dynamic Networks for Covariate Shift Robustness

1 citations · 1 across the 1 of their papers we have counts for

collaborators

8 papers

cs.CV20201 cited

Self-Supervised Dynamic Networks for Covariate Shift Robustness

Tomer Cohen, Noy Shulman, Hai Morgenstern +2

As supervised learning still dominates most AI applications, test-time performance is often unexpected. Specifically, a shift of the input covariates, caused by typical nuisances l…

cs.CV2018

Adversarial Feedback Loop

Firas Shama, Roey Mechrez, Alon Shoshan +1

Thanks to their remarkable generative capabilities, GANs have gained great popularity, and are used abundantly in state-of-the-art methods and applications. In a GAN based model, a…

cs.CV2018

Dynamic-Net: Tuning the Objective Without Re-training for Synthesis Tasks

Alon Shoshan, Roey Mechrez, Lihi Zelnik-Manor

One of the key ingredients for successful optimization of modern CNNs is identifying a suitable objective. To date, the objective is fixed a-priori at training time, and any variat…

cs.CV2018

Improving CNN Training using Disentanglement for Liver Lesion Classification in CT

Avi Ben-Cohen, Roey Mechrez, Noa Yedidia +1

Training data is the key component in designing algorithms for medical image analysis and in many cases it is the main bottleneck in achieving good results. Recent progress in imag…

cs.CV2018

The 2018 PIRM Challenge on Perceptual Image Super-resolution

Yochai Blau, Roey Mechrez, Radu Timofte +2

This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at ECC…

cs.CV2018

Maintaining Natural Image Statistics with the Contextual Loss

Roey Mechrez, Itamar Talmi, Firas Shama +1

Maintaining natural image statistics is a crucial factor in restoration and generation of realistic looking images. When training CNNs, photorealism is usually attempted by adversa…