95 citations · 388 across the 49 of their papers we have counts for
5 papers · 2 filters
Depth Refinement for Improved Stereo Reconstruction
Amit Bracha, Noam Rotstein, David Bensaïd +2
Depth estimation is a cornerstone of a vast number of applications requiring 3D assessment of the environment, such as robotics, augmented reality, and autonomous driving to name a…
Unsupervised High-Fidelity Facial Texture Generation and Reconstruction
Ron Slossberg, Ibrahim Jubran, Ron Kimmel
Many methods have been proposed over the years to tackle the task of facial 3D geometry and texture recovery from a single image. Such methods often fail to provide high-fidelity t…
Multimodal Colored Point Cloud to Image Alignment
Noam Rotstein, Amit Bracha, Ron Kimmel
Reconstruction of geometric structures from images using supervised learning suffers from limited available amount of accurate data. One type of such data is accurate real-world RG…
U-mesh: Human Correspondence Matching with Mesh Convolutional Networks
Benjamin Groisser, Alon Wolf, Ron Kimmel
The proliferation of 3D scanning technology has driven a need for methods to interpret geometric data, particularly for human subjects. In this paper we propose an elegant fusion o…
Provably Approximated ICP
Ibrahim Jubran, Alaa Maalouf, Ron Kimmel +1
The goal of the \emph{alignment problem} is to align a (given) point cloud to another (observed) point cloud . That is, to compute…