Zero-Shot Counting
5 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Zero-shot Object Counting
By applying this model to all the candidate patches, we can select the most suitable patches as exemplars for counting.
CLIP-Count: Towards Text-Guided Zero-Shot Object Counting
Specifically, we propose CLIP-Count, the first end-to-end pipeline that estimates density maps for open-vocabulary objects with text guidance in a zero-shot manner.
Open-world Text-specified Object Counting
Our objective is open-world object counting in images, where the target object class is specified by a text description.
Point, Segment and Count: A Generalized Framework for Object Counting
In this paper, we propose a generalized framework for both few-shot and zero-shot object counting based on detection.
VLCounter: Text-aware Visual Representation for Zero-Shot Object Counting
Zero-Shot Object Counting (ZSOC) aims to count referred instances of arbitrary classes in a query image without human-annotated exemplars.