SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 241–250 of 371 papers

TitleStatusHype
Bayesian Multi Scale Neural Network for Crowd Counting—0
BBA-net: A bi-branch attention network for crowd counting—0
Boosting Adverse Weather Crowd Counting via Multi-queue Contrastive Learning—0
Rethinking Global Context in Crowd Counting—0
Bound Tightening Network for Robust Crowd Counting—0
Calibrating Uncertainty for Semi-Supervised Crowd Counting—0
Cascaded Residual Density Network for Crowd Counting—0
Causal Influence in Federated Edge Inference—0
CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting—0
Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network—0
Show:102550
← PrevPage 25 of 38Next →

No leaderboard results yet.