429 citations · 559 across the 8 of their papers we have counts for
8 papers
Conditional WGANs with Adaptive Gradient Balancing for Sparse MRI Reconstruction
Itzik Malkiel, Sangtae Ahn, Valentina Taviani +3
Recent sparse MRI reconstruction models have used Deep Neural Networks (DNNs) to reconstruct relatively high-quality images from highly undersampled k-space data, enabling much fas…
Vid2Game: Controllable Characters Extracted from Real-World Videos
Oran Gafni, Lior Wolf, Yaniv Taigman
We are given a video of a person performing a certain activity, from which we extract a controllable model. The model generates novel image sequences of that person, according to a…
Improved Stereo Matching with Constant Highway Networks and Reflective Confidence Learning
Amit Shaked, Lior Wolf
We present an improved three-step pipeline for the stereo matching problem and introduce multiple novelties at each stage. We propose a new highway network architecture for computi…
The Loss Surface of Residual Networks: Ensembles and the Role of Batch Normalization
Etai Littwin, Lior Wolf
Deep Residual Networks present a premium in performance in comparison to conventional networks of the same depth and are trainable at extreme depths. It has recently been shown tha…
Unsupervised Cross-Domain Image Generation
Yaniv Taigman, Adam Polyak, Lior Wolf
We study the problem of transferring a sample in one domain to an analog sample in another domain. Given two related domains, S and T, we would like to learn a generative function…
InterpoNet, A brain inspired neural network for optical flow dense interpolation
Shay Zweig, Lior Wolf
Sparse-to-dense interpolation for optical flow is a fundamental phase in the pipeline of most of the leading optical flow estimation algorithms. The current state-of-the-art method…