8 citations · 29 across the 13 of their papers we have counts for
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cs.CV2017
Graph-Cut RANSAC
Daniel Barath, Jiri Matas
A novel method for robust estimation, called Graph-Cut RANSAC, GC-RANSAC in short, is introduced. To separate inliers and outliers, it runs the graph-cut algorithm in the local opt…
cs.CV2017
Multi-Class Model Fitting by Energy Minimization and Mode-Seeking
Daniel Barath, Jiri Matas
We propose a general formulation, called Multi-X, for multi-class multi-instance model fitting - the problem of interpreting the input data as a mixture of noisy observations origi…
cs.CV2017
Working hard to know your neighbor's margins: Local descriptor learning loss
Anastasiya Mishchuk, Dmytro Mishkin, Filip Radenovic +1
We introduce a novel loss for learning local feature descriptors which is inspired by the Lowe's matching criterion for SIFT. We show that the proposed loss that maximizes the dist…