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 301–325 of 371 papers

TitleStatusHype
Depth Information Guided Crowd Counting for Complex Crowd Scenes—0
Diffusion-based Data Augmentation for Object Counting Problems—0
Direct Measure Matching for Crowd Counting—0
Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNN—0
Domain-adaptive Crowd Counting via High-quality Image Translation and Density Reconstruction—0
DroneNet: Crowd Density Estimation using Self-ONNs for Drones—0
EHNet: An Efficient Hybrid Network for Crowd Counting and Localization—0
Embodied Crowd Counting—0
Enhanced 3D convolutional networks for crowd counting—0
Enhanced Information Fusion Network for Crowd Counting—0
Enhancing and Dissecting Crowd Counting By Synthetic Data—0
Enhancing people localisation in drone imagery for better crowd management by utilising every pixel in high-resolution images—0
Exploiting Sample Correlation for Crowd Counting With Multi-Expert Network—0
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance—0
FGA: Fourier-Guided Attention Network for Crowd Count Estimation—0
FGENet: Fine-Grained Extraction Network for Congested Crowd Counting—0
Fine-Grained Counting with Crowd-Sourced Supervision—0
Fine-Grained Crowd Counting—0
Fine-grained Domain Adaptive Crowd Counting via Point-derived Segmentation—0
Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting—0
Fully Convolutional Crowd Counting On Highly Congested Scenes—0
Generalizing semi-supervised generative adversarial networks to regression using feature contrasting—0
Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs—0
Glance to Count: Learning to Rank with Anchors for Weakly-supervised Crowd Counting—0
HA-CCN: Hierarchical Attention-based Crowd Counting Network—0
Show:102550
← PrevPage 13 of 15Next →

No leaderboard results yet.