429 citations · 1.3k across the 86 of their papers we have counts for
7 papers · 2 filters
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…
Temporal Tessellation: A Unified Approach for Video Analysis
Dotan Kaufman, Gil Levi, Tal Hassner +1
We present a general approach to video understanding, inspired by semantic transfer techniques that have been successfully used for 2D image analysis. Our method considers a video…
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…
Optical Flow Requires Multiple Strategies (but only one network)
Tal Schuster, Lior Wolf, David Gadot
We show that the matching problem that underlies optical flow requires multiple strategies, depending on the amount of image motion and other factors. We then study the implication…