1 citations · 1 across the 4 of their papers we have counts for
4 papers
DAVE -- A Detect-and-Verify Paradigm for Low-Shot Counting
Jer Pelhan, Alan Lukežič, Vitjan Zavrtanik +1
Low-shot counters estimate the number of objects corresponding to a selected category, based on only few or no exemplars annotated in the image. The current state-of-the-art estima…
A New Dataset and a Distractor-Aware Architecture for Transparent Object Tracking
Alan Lukezic, Ziga Trojer, Jiri Matas +1
Performance of modern trackers degrades substantially on transparent objects compared to opaque objects. This is largely due to two distinct reasons. Transparent objects are unique…
A Discriminative Single-Shot Segmentation Network for Visual Object Tracking
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…
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…