641 citations · 1.5k across the 32 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…
Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks
Domen Tabernik, Matej Kristan, Aleš Leonardis
Convolutional neural networks excel in a number of computer vision tasks. One of their most crucial architectural elements is the effective receptive field size, that has to be man…