2026
Bootstrapping MLLM for Weakly‑Supervised Class‑Agnostic Object Counting
ICLR 2026poster
Object counting is a fundamental task in computer vision, with broad applicability in many real-world scenarios. Fully-supervised counting methods require costly point-level annotations per object. Few weakly-supervised methods leverage only image-level object counts as supervision and achieve fairl…