Crowd Counting
137 papers with code • 10 benchmarks • 19 datasets
Crowd Counting is a task to count people in image. It is mainly used in real-life for automated public monitoring such as surveillance and traffic control. Different from object detection, Crowd Counting aims at recognizing arbitrarily sized targets in various situations including sparse and cluttering scenes at the same time.
Benchmarks
These leaderboards are used to track progress in Crowd Counting
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Libraries
Use these libraries to find Crowd Counting models and implementationsDatasets
ShanghaiTech
UCF-QNRF
JHU-CROWD++
UCF-CC-50
NWPU-Crowd
JHU-CROWD
Latest papers with no code
Fuss-Free Network: A Simplified and Efficient Neural Network for Crowd Counting
In the field of crowd-counting research, many recent deep learning based methods have demonstrated robust capabilities for accurately estimating crowd sizes.
A Density-Guided Temporal Attention Transformer for Indiscernible Object Counting in Underwater Video
Dense object counting or crowd counting has come a long way thanks to the recent development in the vision community.
Robust Unsupervised Crowd Counting and Localization with Adaptive Resolution SAM
The existing crowd counting models require extensive training data, which is time-consuming to annotate.
Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling
This paper focuses on semi-supervised crowd counting, where only a small portion of the training data are labeled.
Diffusion-based Data Augmentation for Object Counting Problems
Our proposed smoothed density map input for ControlNet significantly improves ControlNet's performance in generating crowds in the correct locations.
Multimodal Crowd Counting with Pix2Pix GANs
Recently, some studies have reported improvement in the accuracy of crowd counting models using a combination of RGB and thermal images.
Curriculum for Crowd Counting -- Is it Worthy?
In this work, we investigate the impact of curriculum learning in crowd counting using the density estimation method.
A Lightweight Feature Fusion Architecture For Resource-Constrained Crowd Counting
However, most of the previous methods rely on a heavy backbone and a complex downstream architecture that restricts the deployment.
FGENet: Fine-Grained Extraction Network for Congested Crowd Counting
Crowd counting has gained significant popularity due to its practical applications.
Scale-Aware Crowd Count Network with Annotation Error Correction
Furthermore, the use of a fixed Gaussian kernel fails to account for the varying pixel distribution with respect to the camera distance.
