This work studies the problem of few-shot object counting, which counts the number of
exemplar objects (ie, described by one or several support images) occurring in the query …

Crowd counting plays a crucial rule in the development of smart city. However, the problems
of scale variations and background interferences degrade the performance of the crowd …

Our objective is open-world object counting in images, where the target object class is
specified by a text description. To this end, we propose CounTX, a class-agnostic, single …

Object counting, defined as the task of accurately predicting the number of objects in static
images or videos, has recently attracted considerable interest. However, the unavoidable …

Mangroves are vital components of coastal ecosystems. Due to the complex canopy
morphology and dense distribution of mangroves, it is challenging to accurately estimate the …

It is important to determine car density in parking lots, especially in hospitals, large
enterprises, and residential areas, which are used intensively, in terms of executing existing …

Object counting is an indispensable task in manufacturing and management. Recently, the
development of image-processing techniques and deep learning object detection has …

As a method of deep learning interpretability, class activation mapping (CAM) is efficient and
convenient for extracting geographic objects supervised by image-level labels. However, in …

The integration of remote sensing object counting in the Mobile Edge Computing (MEC)
environment is of crucial significance and practical value. However, the presence of …

The goal of this paper is to improve the generality and accuracy of open-vocabulary object
counting in images. To improve the generality, we repurpose an open-vocabulary detection …