A Recipe for CAC: Mosaic-based Generalized Loss for Improved Class-Agnostic Counting

arXiv:2404.09826v1 Announce Type: new
Abstract: Class agnostic counting (CAC) is a vision task that can be used to count the total occurrence number of any given reference objects in the query image. The task is usually formulated as a density map estimation problem through similarity computation among a few image samples of the reference object and the query image. In this paper, we point out a severe issue of the existing CAC framework: Given a multi-class setting, models don't consider …

abstract arxiv cac class computation count cs.cv generalized image loss map mosaic objects query recipe reference through total type vision