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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 201–210 of 371 papers

TitleStatusHype
Multi-Level Attentive Convoluntional Neural Network for Crowd Counting—0
Rethinking Global Context in Crowd Counting—0
Crowd Counting by Self-supervised Transfer Colorization Learning and Global Prior Classification—0
Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead—0
Motion-guided Non-local Spatial-Temporal Network for Video Crowd Counting—0
Towards Adversarial Patch Analysis and Certified Defense against Crowd CountingCode0
Multi-Scale Context Aggregation Network with Attention-Guided for Crowd CountingCode0
Multi-channel Deep Supervision for Crowd Counting—0
Weight Rescaling: Effective and Robust Regularization for Deep Neural Networks with Batch Normalization—0
Spatiotemporal Dilated Convolution with Uncertain Matching for Video-based Crowd EstimationCode0
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