641 citations · 3k across the 58 of their papers we have counts for
17 papers · 2 filters
MAGSAC++, a fast, reliable and accurate robust estimator
Daniel Barath, Jana Noskova, Maksym Ivashechkin +1
A new method for robust estimation, MAGSAC++, is proposed. It introduces a new model quality (scoring) function that does not require the inlier-outlier decision, and a novel margi…
DAL -- A Deep Depth-aware Long-term Tracker
Yanlin Qian, Alan Lukežič, Matej Kristan +2
The best RGBD trackers provide high accuracy but are slow to run. On the other hand, the best RGB trackers are fast but clearly inferior on the RGBD datasets. In this work, we prop…
Sub-frame Appearance and 6D Pose Estimation of Fast Moving Objects
Denys Rozumnyi, Jan Kotera, Filip Sroubek +1
We propose a novel method that tracks fast moving objects, mainly non-uniform spherical, in full 6 degrees of freedom, estimating simultaneously their 3D motion trajectory, 3D pose…
D3S -- A Discriminative Single Shot Segmentation Tracker
Alan Lukežič, Jiří Matas, Matej Kristan
Template-based discriminative trackers are currently the dominant tracking paradigm due to their robustness, but are restricted to bounding box tracking and a limited range of tran…
Non-Causal Tracking by Deblatting
Denys Rozumnyi, Jan Kotera, Filip Šroubek +1
Tracking by Deblatting stands for solving an inverse problem of deblurring and image matting for tracking motion-blurred objects. We propose non-causal Tracking by Deblatting which…
Visual Coin-Tracking: Tracking of Planar Double-Sided Objects
Jonáš Šerých, Jiří Matas
We introduce a new video analysis problem -- tracking of rigid planar objects in sequences where both their sides are visible. Such coin-like objects often rotate fast with respect…
ALFA: Agglomerative Late Fusion Algorithm for Object Detection
Evgenii Razinkov, Iuliia Saveleva, Jiři Matas
We propose ALFA - a novel late fusion algorithm for object detection. ALFA is based on agglomerative clustering of object detector predictions taking into consideration both the bo…
ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition -- RRC-MLT-2019
Nibal Nayef, Yash Patel, Michal Busta +8
With the growing cosmopolitan culture of modern cities, the need of robust Multi-Lingual scene Text (MLT) detection and recognition systems has never been more immense. With the go…
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark
Alan Lukežič, Ugur Kart, Jani Käpylä +4
A long-term visual object tracking performance evaluation methodology and a benchmark are proposed. Performance measures are designed by following a long-term tracking definition t…
Intra-frame Object Tracking by Deblatting
Jan Kotera, Denys Rozumnyi, Filip Šroubek +1
Objects moving at high speed along complex trajectories often appear in videos, especially videos of sports. Such objects elapse non-negligible distance during exposure time of a s…
Performance Evaluation Methodology for Long-Term Visual Object Tracking
Alan Lukežič, Luka Čehovin Zajc, Tomáš Vojíř +2
A long-term visual object tracking performance evaluation methodology and a benchmark are proposed. Performance measures are designed by following a long-term tracking definition t…
Progressive NAPSAC: sampling from gradually growing neighborhoods
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. Exploiting the f…
Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithm
Daniel Barath, Jiri Matas
The Progressive-X algorithm, Prog-X in short, is proposed for geometric multi-model fitting. The method interleaves sampling and consolidation of the current data interpretation vi…
Rolling Shutter Camera Synchronization with Sub-millisecond Accuracy
Matej Smid, Jiri Matas
A simple method for synchronization of video streams with a precision better than one millisecond is proposed. The method is applicable to any number of rolling shutter cameras and…
Flash Lightens Gray Pixels
Yanlin Qian, Song Yan, Joni-Kristian Kämäräinen +1
In the real world, a scene is usually cast by multiple illuminants and herein we address the problem of spatial illumination estimation. Our solution is based on detecting gray pix…
Leveraging Outdoor Webcams for Local Descriptor Learning
Milan Pultar, Dmytro Mishkin, Jiří Matas
We present AMOS Patches, a large set of image cut-outs, intended primarily for the robustification of trainable local feature descriptors to illumination and appearance changes. Im…
On Finding Gray Pixels
Yanlin Qian, Joni-Kristian Kämäräinen, Jarno Nikkanen +1
We propose a novel grayness index for finding gray pixels and demonstrate its effectiveness and efficiency in illumination estimation. The grayness index, GI in short, is derived u…