From the 1 of 4 linked papers with an AI index.
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CoDi -- an exemplar-conditioned diffusion model for low-shot counting
Grega Å uÅ¡tar, Jer Pelhan, Alan LukežiÄ +1
CoDi is a latent diffusion-based model that uses exemplar-conditioned conditioning to generate high-quality density maps for low-shot object counting, enabling accurate object loca…
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 LukežiÄ, 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 LukežiÄ, 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…