Crowd Counting

71 papers with code • 6 benchmarks • 14 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.

Source: Deep Density-aware Count Regressor

Latest papers with code

VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results

shizenglin/Counting-with-Focus-for-Free 19 Jul 2021

Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.

Crowd Counting Platform

19 Jul 2021

Crowd Counting via Perspective-Guided Fractional-Dilation Convolution

Zhaoyi-Yan/PFDNet 8 Jul 2021

One of the main issues in this task is how to handle the dramatic scale variations of pedestrians caused by the perspective effect.

Crowd Counting

08 Jul 2021

Deep learning with self-supervision and uncertainty regularization to count fish in underwater images

ptarling/DeepLearningFishCounting 30 Apr 2021

From experiments on both contrasting datasets, we demonstrate our network outperforms the few other deep learning models implemented for solving this task.

Crowd Counting Decision Making

30 Apr 2021

Dense Point Prediction: A Simple Baseline for Crowd Counting and Localization

WangyiNTU/SCALNet 26 Apr 2021

In this paper, we propose a simple yet effective crowd counting and localization network named SCALNet.

Crowd Counting

26 Apr 2021

Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting

harrywuhust2022/Adv-Crowd-analysis 22 Apr 2021

To better enhance the adversarial robustness of crowd counting models, we propose the first regression model-based Randomized Ablation (RA), which is more sufficient than Adversarial Training (ADT) (Mean Absolute Error of RA is 5 lower than ADT on clean samples and 30 lower than ADT on adversarial examples).

Adversarial Attack Crowd Counting +1

22 Apr 2021

TransCrowd: Weakly-Supervised Crowd Counting with Transformer

dk-liang/TransCrowd 19 Apr 2021

Current weakly-supervised counting methods adopt the CNN to regress a total count of the crowd by an image-to-count paradigm.

Crowd Counting

19 Apr 2021

Multi-Scale Context Aggregation Network with Attention-Guided for Crowd Counting

KingMV/MSCANet 6 Apr 2021

In this paper, we propose a multi-scale context aggregation network (MSCANet) based on single-column encoder-decoder architecture for crowd counting, which consists of an encoder based on a dense context-aware module (DCAM) and a hierarchical attention-guided decoder.

Crowd Counting

06 Apr 2021

Focal Inverse Distance Transform Maps for Crowd Localization and Counting in Dense Crowd

dk-liang/FIDTM 16 Feb 2021

In this paper, we propose a novel map for dense crowd localization and crowd counting.

Crowd Counting

16 Feb 2021

Spatiotemporal Dilated Convolution with Uncertain Matching for Video-based Crowd Estimation

STDNet/STDNet 29 Jan 2021

In this paper, we propose a novel SpatioTemporal convolutional Dense Network (STDNet) to address the video-based crowd counting problem, which contains the decomposition of 3D convolution and the 3D spatiotemporal dilated dense convolution to alleviate the rapid growth of the model size caused by the Conv3D layer.

Crowd Counting

29 Jan 2021

CNN-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal

HaoyueBaiZJU/A-Recent-Systematic-Survey-for-Crowd-Counting 31 Dec 2020

Single image crowd counting is a challenging computer vision problem with wide applications in public safety, city planning, traffic management, etc.

Crowd Counting

31 Dec 2020