704 citations · 3.6k across the 98 of their papers we have counts for
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A Self Supervised StyleGAN for Image Annotation and Classification with Extremely Limited Labels
Dana Cohen Hochberg, Hayit Greenspan, Raja Giryes
The recent success of learning-based algorithms can be greatly attributed to the immense amount of annotated data used for training. Yet, many datasets lack annotations due to the…
3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI
Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea +2
Self-supervised models allow (pre-)training on unlabeled data and therefore have the potential to overcome the need for large annotated cohorts. One leading self-supervised model i…
Denoiser-based projections for 2-D super-resolution multi-reference alignment
Jonathan Shani, Tom Tirer, Raja Giryes +1
We study the 2-D super-resolution multi-reference alignment (SR-MRA) problem: estimating an image from its down-sampled, circularly-translated, and noisy copies. The SR-MRA problem…
Video Reconstruction from a Single Motion Blurred Image using Learned Dynamic Phase Coding
Erez Yosef, Shay Elmalem, Raja Giryes
Video reconstruction from a single motion-blurred image is a challenging problem, which can enhance the capabilities of existing cameras. Recently, several works addressed this tas…
MISS GAN: A Multi-IlluStrator Style Generative Adversarial Network for image to illustration translation
Noa Barzilay, Tal Berkovitz Shalev, Raja Giryes
Unsupervised style transfer that supports diverse input styles using only one trained generator is a challenging and interesting task in computer vision. This paper proposes a Mult…
An Interpretation of Regularization by Denoising and its Application with the Back-Projected Fidelity Term
Einav Yogev-Ofer, Tom Tirer, Raja Giryes
The vast majority of image recovery tasks are ill-posed problems. As such, methods that are based on optimization use cost functions that consist of both fidelity and prior (regula…
BP-DIP: A Backprojection based Deep Image Prior
Jenny Zukerman, Tom Tirer, Raja Giryes
Deep neural networks are a very powerful tool for many computer vision tasks, including image restoration, exhibiting state-of-the-art results. However, the performance of deep lea…
Motion Deblurring using Spatiotemporal Phase Aperture Coding
Shay Elmalem, Raja Giryes, Emanuel Marom
Motion blur is a known issue in photography, as it limits the exposure time while capturing moving objects. Extensive research has been carried to compensate for it. In this work,…
Image-Adaptive GAN based Reconstruction
Shady Abu Hussein, Tom Tirer, Raja Giryes
In the recent years, there has been a significant improvement in the quality of samples produced by (deep) generative models such as variational auto-encoders and generative advers…
A Greedy Approach to Based Convolutional Sparse Coding
Elad Plaut, Raja Giryes
Sparse coding techniques for image processing traditionally rely on a processing of small overlapping patches separately followed by averaging. This has the disadvantage that the r…
DeepISP: Towards Learning an End-to-End Image Processing Pipeline
Eli Schwartz, Raja Giryes, Alex M. Bronstein
We present DeepISP, a full end-to-end deep neural model of the camera image signal processing (ISP) pipeline. Our model learns a mapping from the raw low-light mosaiced image to th…