3 citations · 4 across the 3 of their papers we have counts for
5 papers
UGO: Unified Architecture for General Multi-Object Tracking by Segmentation
Jer Pelhan, Alan Lukezic, Matej Kristan
General multi-object tracking (GMOT) tracks all instances of a user-specified category from a single first-frame exemplar. Prior work relies on bounding boxes and surrogate trainin…
CoDi -- an exemplar-conditioned diffusion model for low-shot counting
Grega Šuštar, Jer Pelhan, Alan Lukežič +1
Low-shot object counting addresses estimating the number of previously unobserved objects in an image using only few or no annotated test-time exemplars. A considerable challenge f…
Generalized-Scale Object Counting with Gradual Query Aggregation
Jer Pelhan, Alan Lukezic, Matej Kristan
Few-shot detection-based counters estimate the number of instances in the image specified only by a few test-time exemplars. A common approach to localize objects across multiple s…
A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation
Jer Pelhan, Alan Lukežič, Vitjan Zavrtanik +1
Low-shot object counters estimate the number of objects in an image using few or no annotated exemplars. Objects are localized by matching them to prototypes, which are constructed…
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…