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no code implementations • 28 Nov 2021 • Wei Tong, Jiri Matas, Daniel Barath

We propose Deep MAGSAC++ combining the advantages of traditional and deep robust estimators.

no code implementations • 24 Nov 2021 • Daniel Barath, Gabor Valasek

A new algorithm is proposed to accelerate RANSAC model quality calculations.

no code implementations • ICCV 2021 • Maksym Ivashechkin, Daniel Barath, Jiri Matas

Experiments on four standard datasets show that VSAC is significantly faster than all its predecessors and runs on average in 1-2 ms, on a CPU.

no code implementations • 11 Apr 2021 • Maksym Ivashechkin, Daniel Barath, Jiri Matas

We review the most recent RANSAC-like hypothesize-and-verify robust estimators.

no code implementations • 25 Mar 2021 • Daniel Barath, Denys Rozumny, Ivan Eichhardt, Levente Hajder, Jiri Matas

We propose Progressive-X+, a new algorithm for finding an unknown number of geometric models, e. g., homographies.

1 code implementation • ICCV 2021 • Snehal Bhayani, Torsten Sattler, Daniel Barath, Patrik Beliansky, Janne Heikkila, Zuzana Kukelova

In this paper, we propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera.

no code implementations • CVPR 2021 • Yaqing Ding, Daniel Barath, Jian Yang, Hui Kong, Zuzana Kukelova

Smartphones, tablets and camera systems used, e. g., in cars and UAVs, are typically equipped with IMUs (inertial measurement units) that can measure the gravity vector accurately.

no code implementations • ICCV 2021 • Yaqing Ding, Daniel Barath, Zuzana Kukelova

When capturing panoramas, people tend to align their cameras with the vertical axis, i. e., the direction of gravity.

no code implementations • CVPR 2021 • Daniel Barath, Dmytro Mishkin, Ivan Eichhardt, Ilia Shipachev, Jiri Matas

We propose ways to speed up the initial pose-graph generation for global Structure-from-Motion algorithms.

no code implementations • 13 Aug 2020 • Istan Gergo Gal, Daniel Barath, Levente Hajder

For the first class of solvers, the sought plane is expected to be perpendicular to one of the camera axes.

no code implementations • ICCV 2021 • Banglei Guan, Ji Zhao, Daniel Barath, Friedrich Fraundorfer

We propose three novel solvers for estimating the relative pose of a multi-camera system from affine correspondences (ACs).

1 code implementation • ECCV 2020 • Daniel Barath, Michal Polic, Wolfgang Förstner, Torsten Sattler, Tomas Pajdla, Zuzana Kukelova

The main advantage of such solvers is that their sample size is smaller, e. g., only two instead of four matches are required to estimate a homography.

1 code implementation • ECCV 2020 • Ivan Eichhardt, Daniel Barath

We propose a new approach for combining deep-learned non-metric monocular depth with affine correspondences (ACs) to estimate the relative pose of two calibrated cameras from a single correspondence.

1 code implementation • CVPR 2020 • Tomas Hodan, Daniel Barath, Jiri Matas

A data-dependent number of corresponding 3D locations is selected per pixel, and poses of possibly multiple object instances are estimated using a robust and efficient variant of the PnP-RANSAC algorithm.

no code implementations • 13 Dec 2019 • Levente Hajder, Daniel Barath

A new closed-form solver is proposed minimizing the algebraic error optimally, in the least-squares sense, to estimate the relative planar motion of two calibrated cameras.

no code implementations • 13 Dec 2019 • Levente Hajder, Daniel Barath

A new minimal solver is proposed for the semi-calibrated case, i. e. the camera parameters are known except a common focal length.

no code implementations • CVPR 2020 • Daniel Barath, Jana Noskova, Maksym Ivashechkin, Jiri Matas

A new method for robust estimation, MAGSAC++, is proposed.

1 code implementation • ICCV 2019 • Daniel Barath, Zuzana Kukelova

Two new general constraints are derived on the scales and rotations which can be used in any geometric model estimation tasks.

2 code implementations • ICCV 2019 • Daniel Barath, Jiri Matas

The Progressive-X algorithm, Prog-X in short, is proposed for geometric multi-model fitting.

no code implementations • 5 Jun 2019 • Daniel Barath, Maksym Ivashechkin, Jiri Matas

We propose Progressive NAPSAC, P-NAPSAC in short, which merges the advantages of local and global sampling by drawing samples from gradually growing neighborhoods.

1 code implementation • 1 May 2019 • Ivan Eichhardt, Daniel Barath

The technique requires the epipolar geometry to be pre-estimated between each image pair.

1 code implementation • 10 Jul 2018 • Daniel Barath

An approach is proposed for recovering affine correspondences (ACs) from orientation- and scale-invariant, e. g. SIFT, features.

2 code implementations • CVPR 2019 • Daniel Barath, Jana Noskova, Jiri Matas

A method called, sigma-consensus, is proposed to eliminate the need for a user-defined inlier-outlier threshold in RANSAC.

no code implementations • CVPR 2018 • Daniel Barath

We aim at estimating the fundamental matrix in two views from five correspondences of rotation invariant features obtained by e. g.\ the SIFT detector.

no code implementations • CVPR 2017 • Daniel Barath, Tekla Toth, Levente Hajder

To select the best one out of the remaining candidates, a root selection technique is proposed outperforming the recent ones especially in case of high-level noise.

1 code implementation • CVPR 2018 • Daniel Barath, Jiri Matas

A novel method for robust estimation, called Graph-Cut RANSAC, GC-RANSAC in short, is introduced.

1 code implementation • ECCV 2018 • Daniel Barath, Jiri Matas

The move replaces a set of labels with the corresponding density mode in the model parameter domain, thus achieving fast and robust optimization.

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