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20132022
most citedSingle View Depth Estimation from Examples

17 citations · 35 across the 8 of their papers we have counts for

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9 papers · 1 filter

cs.CV2021

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…

cs.CV20216 cited

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…

cs.CV2019

Averaging Essential and Fundamental Matrices in Collinear Camera Settings

Amnon Geifman, Yoni Kasten, Meirav Galun +1

Global methods to Structure from Motion have gained popularity in recent years. A significant drawback of global methods is their sensitivity to collinear camera settings. In this…

cs.CV2019

Algebraic Characterization of Essential Matrices and Their Averaging in Multiview Settings

Yoni Kasten, Amnon Geifman, Meirav Galun +1

Essential matrix averaging, i.e., the task of recovering camera locations and orientations in calibrated, multiview settings, is a first step in global approaches to Euclidean stru…

cs.CV20193 cited

Resultant Based Incremental Recovery of Camera Pose from Pairwise Matches

Yoni Kasten, Meirav Galun, Ronen Basri

Incremental (online) structure from motion pipelines seek to recover the camera matrix associated with an image given images, , whose camera matrices h…

cs.CV20173 cited

A New Rank Constraint on Multi-view Fundamental Matrices, and its Application to Camera Location Recovery

Soumyadip Sengupta, Tal Amir, Meirav Galun +4

Accurate estimation of camera matrices is an important step in structure from motion algorithms. In this paper we introduce a novel rank constraint on collections of fundamental ma…