11 citations · 41 across the 38 of their papers we have counts for
6 papers · 2 filters
Rethinking FUN: Frequency-Domain Utilization Networks
Kfir Goldberg, Stav Shapiro, Elad Richardson +1
The search for efficient neural network architectures has gained much focus in recent years, where modern architectures focus not only on accuracy but also on inference time and mo…
Geometric Adversarial Attacks and Defenses on 3D Point Clouds
Itai Lang, Uriel Kotlicki, Shai Avidan
Deep neural networks are prone to adversarial examples that maliciously alter the network's outcome. Due to the increasing popularity of 3D sensors in safety-critical systems and t…
Dual Geometric Graph Network (DG2N) -- Iterative network for deformable shape alignment
Dvir Ginzburg, Dan Raviv
We provide a novel new approach for aligning geometric models using a dual graph structure where local features are mapping probabilities. Alignment of non-rigid structures is one…
Best Buddies Registration for Point Clouds
Amnon Drory, Tal Shomer, Shai Avidan +1
We propose new, and robust, loss functions for the point cloud registration problem. Our loss functions are inspired by the Best Buddies Similarity (BBS) measure that counts the nu…
Co-occurrence Based Texture Synthesis
Anna Darzi, Itai Lang, Ashutosh Taklikar +2
As image generation techniques mature, there is a growing interest in explainable representations that are easy to understand and intuitive to manipulate. In this work, we turn to…
Deep Image Compression using Decoder Side Information
Sharon Ayzik, Shai Avidan
We present a Deep Image Compression neural network that relies on side information, which is only available to the decoder. We base our algorithm on the assumption that the image a…