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 126–150 of 371 papers

TitleStatusHype
DR.VIC: Decomposition and Reasoning for Video Individual CountingCode1
CrowdMLP: Weakly-Supervised Crowd Counting via Multi-Granularity MLP—0
Joint CNN and Transformer Network via weakly supervised Learning for efficient crowd counting—0
CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability—0
Boosting Crowd Counting via Multifaceted AttentionCode1
FusionCount: Efficient Crowd Counting via Multiscale Feature FusionCode1
Reinforcing Local Feature Representation for Weakly-Supervised Dense Crowd Counting—0
Multiscale Crowd Counting and Localization By Multitask Point SupervisionCode1
TAFNet: A Three-Stream Adaptive Fusion Network for RGB-T Crowd CountingCode0
A Unified Multi-Task Learning Framework of Real-Time Drone Supervision for Crowd Counting—0
Enhancing and Dissecting Crowd Counting By Synthetic Data—0
Few-shot Object Counting with Similarity-Aware Feature EnhancementCode1
BBA-net: A bi-branch attention network for crowd counting—0
Deep Rank-Consistent Pyramid Model for Enhanced Crowd CountingCode1
Crowd Counting in the Frequency DomainCode1
Scene-Adaptive Attention Network for Crowd Counting—0
Towards More Effective PRM-based Crowd Counting via A Multi-resolution Fusion and Attention Network—0
Panoptic Segmentation: A ReviewCode1
PANet: Perspective-Aware Network with Dynamic Receptive Fields and Self-Distilling Supervision for Crowd Counting—0
International Workshop on Continual Semi-Supervised Learning: Introduction, Benchmarks and Baselines—0
Vicinal Counting Networks—0
CCTrans: Simplifying and Improving Crowd Counting with TransformerCode1
Harnessing Perceptual Adversarial Patches for Crowd CountingCode1
Audio-Visual Transformer Based Crowd Counting—0
Semi-Supervised Crowd Counting from Unlabeled Data—0
Show:102550
← PrevPage 6 of 15Next →

No leaderboard results yet.