6 citations · 13 across the 8 of their papers we have counts for
15 papers · 1 filter
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…
Distractor-Aware Memory-Based Visual Object Tracking
Jovana Videnovic, Matej Kristan, Alan Lukezic
Recent emergence of memory-based video segmentation methods such as SAM2 has led to models with excellent performance in segmentation tasks, achieving leading results on numerous b…
A Distractor-Aware Memory for Visual Object Tracking with SAM2
Jovana Videnovic, Alan Lukezic, Matej Kristan
Memory-based trackers are video object segmentation methods that form the target model by concatenating recently tracked frames into a memory buffer and localize the target by atte…
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…