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Crowds

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AaronCIH/APGCC

공식 코드

Improving Point-based Crowd Counting and Localization Based on Auxiliary Point Guidance

https://github.com/GeorgeChenZJ/deepcount

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Deep Density-aware Count Regressor

https://github.com/HCPLab-SYSU/SKT

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Efficient Crowd Counting via Structured Knowledge Transfer

https://github.com/HaoyueBaiZJU/A-Recent-Systematic-Survey-for-Crowd-Counting

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A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal

https://github.com/JunhaoCheng/Pyramid_Scale_Network

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Exploit the potential of Multi-column architecture for Crowd Counting

https://github.com/KaimingHe/resnet-1k-layers

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Deep Residual Learning for Image Recognition

https://github.com/KingMV/MSCANet

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Multi-Scale Context Aggregation Network with Attention-Guided for Crowd Counting

https://github.com/LoraLinH/Gramformer

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Gramformer: Learning Crowd Counting via Graph-Modulated Transformer

https://github.com/MandyMo/ECCV_Countformer

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CountFormer: Multi-View Crowd Counting Transformer

https://github.com/Pongpisit-Thanasutives/Variations-of-SFANet-for-Crowd-Counting

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Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting

https://github.com/RQuispeC/multi-stream-crowd-counting-extended

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Multi-Stream Networks and Ground-Truth Generation for Crowd Counting

https://github.com/STDNet/STDNet

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Spatiotemporal Dilated Convolution with Uncertain Matching for Video-based Crowd Estimation

https://github.com/TencentYoutuResearch/CrowdCounting-SASNet

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Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting

https://github.com/TopoXLab/TopoCount

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Localization in the Crowd with Topological Constraints

https://github.com/VisDrone/DroneCrowd

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Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark

https://github.com/WangyiNTU/Point-supervised-crowd-detection

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A Self-Training Approach for Point-Supervised Object Detection and Counting in Crowds

https://github.com/WangyiNTU/SCALNet

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Dense Point Prediction: A Simple Baseline for Crowd Counting and Localization

https://github.com/Willy0919/CODA

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CODA: Counting Objects via Scale-aware Adversarial Density Adaption

https://github.com/Yiming-M/CLIP-EBC

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CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification

https://github.com/YimingMa/FusionCount

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FusionCount: Efficient Crowd Counting via Multiscale Feature Fusion

https://github.com/ZPDu/Domain-general-Crowd-Counting-in-Unseen-Scenarios

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Domain-General Crowd Counting in Unseen Scenarios

https://github.com/ZPDu/Redesigning-Multi-Scale-Neural-Network-for-Crowd-Counting

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Redesigning Multi-Scale Neural Network for Crowd Counting

https://github.com/Zhaoyi-Yan/PFDNet

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Crowd Counting via Perspective-Guided Fractional-Dilation Convolution

https://github.com/Zhaoyi-Yan/PGCNet

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Perspective-Guided Convolution Networks for Crowd Counting

https://github.com/ZhihengCV/Baysian-Crowd-Counting

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Bayesian Loss for Crowd Count Estimation with Point Supervision

https://github.com/adrian-dalessandro/SYRAC

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SYRAC: Synthesize, Rank, and Count

https://github.com/atmacvit/bincrowd

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Wisdom of (Binned) Crowds: A Bayesian Stratification Paradigm for Crowd Counting

https://github.com/bingshuangzhuzi/ndconv

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An Improved Normed-Deformable Convolution for Crowd Counting

https://github.com/bridgeqiqi/dream

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Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting

https://github.com/bridgeqiqi/s2fpr

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Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting

https://github.com/cha15yq/MRC-Crowd

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Semi-Supervised Crowd Counting with Contextual Modeling: Facilitating Holistic Understanding of Crowd Scenes

https://github.com/chen-judge/RGBTCrowdCounting

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Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

https://github.com/cptpirx/vcc-compression

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Analysis of the Effect of Low-Overhead Lossy Image Compression on the Performance of Visual Crowd Counting for Smart City Applications

https://github.com/csguomy/mdknet

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Virtual Classification: Modulating Domain-Specific Knowledge for Multidomain Crowd Counting

https://github.com/cvlab-stonybrook/DM-Count

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Distribution Matching for Crowd Counting

https://github.com/cvlab-stonybrook/UncertaintyCrowdCounting

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Uncertainty Estimation and Sample Selection for Crowd Counting

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