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 251–260 of 371 papers

TitleStatusHype
CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting—0
Domain-adaptive Crowd Counting via High-quality Image Translation and Density Reconstruction—0
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance—0
Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention NetworkCode1
Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting—0
Crowd Counting via Segmentation Guided Attention Networks and Curriculum LossCode0
Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method—0
Relational Attention Network for Crowd Counting—0
Attentional Neural Fields for Crowd Counting—0
Adaptive Density Map Generation for Crowd Counting—0
Show:102550
← PrevPage 26 of 38Next →

No leaderboard results yet.