14 citations · 24 across the 2 of their papers we have counts for
8 papers
From Discrete to Continuous Convolution Layers
Assaf Shocher, Ben Feinstein, Niv Haim +1
A basic operation in Convolutional Neural Networks (CNNs) is spatial resizing of feature maps. This is done either by strided convolution (donwscaling) or transposed convolution (u…
SpeedNet: Learning the Speediness in Videos
Sagie Benaim, Ariel Ephrat, Oran Lang +5
We wish to automatically predict the "speediness" of moving objects in videos---whether they move faster, at, or slower than their "natural" speed. The core component in our approa…
Semantic Pyramid for Image Generation
Assaf Shocher, Yossi Gandelsman, Inbar Mosseri +4
We present a novel GAN-based model that utilizes the space of deep features learned by a pre-trained classification model. Inspired by classical image pyramid representations, we c…
Blind Super-Resolution Kernel Estimation using an Internal-GAN
Sefi Bell-Kligler, Assaf Shocher, Michal Irani
Super resolution (SR) methods typically assume that the low-resolution (LR) image was downscaled from the unknown high-resolution (HR) image by a fixed 'ideal' downscaling kernel (…
Natural and Adversarial Error Detection using Invariance to Image Transformations
Yuval Bahat, Michal Irani, Gregory Shakhnarovich
We propose an approach to distinguish between correct and incorrect image classifications. Our approach can detect misclassifications which either occur ("na…
"Double-DIP": Unsupervised Image Decomposition via Coupled Deep-Image-Priors
Yossi Gandelsman, Assaf Shocher, Michal Irani
Many seemingly unrelated computer vision tasks can be viewed as a special case of image decomposition into separate layers. For example, image segmentation (separation into foregro…