641 citations · 1.5k across the 32 of their papers we have counts for
5 papers · 1 filter
Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking
Luka Čehovin Zajc, Alan Lukežič, Aleš Leonardis +1
Object-to-camera motion produces a variety of apparent motion patterns that significantly affect performance of short-term visual trackers. Despite being crucial for designing robu…
Discriminative Correlation Filter with Channel and Spatial Reliability
Alan Lukežič, Tomáš Vojíř, Luka Čehovin +2
Short-term tracking is an open and challenging problem for which discriminative correlation filters (DCF) have shown excellent performance. We introduce the channel and spatial rel…
Towards Deep Compositional Networks
Domen Tabernik, Matej Kristan, Jeremy L. Wyatt +1
Hierarchical feature learning based on convolutional neural networks (CNN) has recently shown significant potential in various computer vision tasks. While allowing high-quality di…
Deformable Parts Correlation Filters for Robust Visual Tracking
Alan Lukežič, Luka Čehovin, Matej Kristan
Deformable parts models show a great potential in tracking by principally addressing non-rigid object deformations and self occlusions, but according to recent benchmarks, they oft…
A regularization-based approach for unsupervised image segmentation
Aleksandar Dimitriev, Matej Kristan
We propose a novel unsupervised image segmentation algorithm, which aims to segment an image into several coherent parts. It requires no user input, no supervised learning phase an…