2 citations · 3 across the 5 of their papers we have counts for
5 papers
Learning Global Camera Poses from Noisy View-Graphs for Structure from Motion
Fadi Khatib, Meirav Galun, Ronen Basri
Camera pose estimation is a key step in 3D reconstruction and view-synthesis pipelines. We present a deep, global Structure-from-Motion framework based on learned view-graph aggreg…
GSVisLoc: Generalizable Visual Localization for Gaussian Splatting Scene Representations
Fadi Khatib, Dror Moran, Guy Trostianetsky +3
We introduce GSVisLoc, a visual localization method designed for 3D Gaussian Splatting (3DGS) scene representations. Given a 3DGS model of a scene and a query image, our goal is to…
Consensus Learning with Deep Sets for Essential Matrix Estimation
Dror Moran, Yuval Margalit, Guy Trostianetsky +3
Robust estimation of the essential matrix, which encodes the relative position and orientation of two cameras, is a fundamental step in structure from motion pipelines. Recent deep…
RESfM: Robust Deep Equivariant Structure from Motion
Fadi Khatib, Yoni Kasten, Dror Moran +2
Multiview Structure from Motion is a fundamental and challenging computer vision problem. A recent deep-based approach utilized matrix equivariant architectures for simultaneous re…
Leveraging Image Matching Toward End-to-End Relative Camera Pose Regression
Fadi Khatib, Yuval Margalit, Meirav Galun +1
This paper proposes a generalizable, end-to-end deep learning-based method for relative pose regression between two images. Given two images of the same scene captured from differe…