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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 111–120 of 371 papers

TitleStatusHype
Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation—0
An Improved Normed-Deformable Convolution for Crowd CountingCode0
Indirect-Instant Attention Optimization for Crowd Counting in Dense Scenes—0
Reducing Capacity Gap in Knowledge Distillation with Review Mechanism for Crowd CountingCode0
Rethinking Spatial Invariance of Convolutional Networks for Object CountingCode1
Self-supervised Domain Adaptation in Crowd Counting—0
Glance to Count: Learning to Rank with Anchors for Weakly-supervised Crowd Counting—0
Fine-Grained Counting with Crowd-Sourced Supervision—0
Bi-level Alignment for Cross-Domain Crowd CountingCode1
Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting—0
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