7 citations · 25 across the 10 of their papers we have counts for
12 papers · 1 filter
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…
Deep Permutation Equivariant Structure from Motion
Dror Moran, Hodaya Koslowsky, Yoni Kasten +3
Existing deep methods produce highly accurate 3D reconstructions in stereo and multiview stereo settings, i.e., when cameras are both internally and externally calibrated. Neverthe…
Segmenting Microcalcifications in Mammograms and its Applications
Roee Zamir, Shai Bagon, David Samocha +3
Microcalcifications are small deposits of calcium that appear in mammograms as bright white specks on the soft tissue background of the breast. Microcalcifications may be a unique…