49 citations · 49 across the 1 of their papers we have counts for
4 papers
DPDist : Comparing Point Clouds Using Deep Point Cloud Distance
Dahlia Urbach, Yizhak Ben-Shabat, Michael Lindenbaum
We introduce a new deep learning method for point cloud comparison. Our approach, named Deep Point Cloud Distance (DPDist), measures the distance between the points in one cloud an…
DeepFit: 3D Surface Fitting via Neural Network Weighted Least Squares
Yizhak Ben-Shabat, Stephen Gould
We propose a surface fitting method for unstructured 3D point clouds. This method, called DeepFit, incorporates a neural network to learn point-wise weights for weighted least squa…
Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks
Yizhak Ben-Shabat, Michael Lindenbaum, Anath Fischer
In this paper, we propose a normal estimation method for unstructured 3D point clouds. This method, called Nesti-Net, builds on a new local point cloud representation which consist…
3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks
Yizhak Ben-Shabat, Michael Lindenbaum, Anath Fischer
The point cloud is gaining prominence as a method for representing 3D shapes, but its irregular format poses a challenge for deep learning methods. The common solution of transform…