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Crowd Counting

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

Papers

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Showing 81–90 of 371 papers

TitleStatusHype
Efficient Crowd Counting via Structured Knowledge TransferCode1
Encoder-Decoder Based Convolutional Neural Network with Multi-Scale-Aware Modules for Crowd CountingCode1
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd CountingCode1
Few-Shot Scene Adaptive Crowd Counting Using Meta-LearningCode1
Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention NetworkCode1
From Open Set to Closed Set: Counting Objects by Spatial Divide-and-ConquerCode1
Densely Connected Convolutional NetworksCode1
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image SegmentationCode1
Car Object Counting and Position Estimation via Extension of the CLIP-EBC FrameworkCode0
Point-to-Region Loss for Semi-Supervised Point-Based Crowd CountingCode0
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