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Crowd Counting
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pszemraj/BoulderAreaDetector
https://github.com/pudae/tensorflow-densenet
https://github.com/pxq0312/ASD-crowd-counting
https://github.com/pxq0312/SFANet-crowd-counting
Dual Path Multi-Scale Fusion Networks with Attention for Crowd Counting
https://github.com/pyaf/DenseNet-MURA-PyTorch
https://github.com/pytorch/vision
https://github.com/pytorch/vision/blob/main/torchvision/models/densenet.py
https://github.com/qubvel/efficientnet
https://github.com/qubvel/resnet_152
https://github.com/rafaelmata357/Flower-image-classifier
https://github.com/raghakot/keras-resnet
https://github.com/rahul-t-p/ASVspoof-2019
https://github.com/rahulchaurasiya1/cautious-waddle
https://github.com/rajkumargithub/densenet.mura
https://github.com/rajneeshaggarwal/google-efficientnet
https://github.com/raywang335/l2rclip
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model
https://github.com/realmichaelye/Skin-Lesions-Classifier-ResNet50
https://github.com/researchmm/SiamDW
https://github.com/rickyHong/tfRecord-Caltech256-repl2
https://github.com/rishabmallick/Sign-language-live-predictor
https://github.com/robertofranceschi/Image-classification-on-Caltech101-using-CNNs
https://github.com/rongliangzi/Dense-Scale-Network-for-Crowd-Counting
https://github.com/rotemgoren/segNet
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/rtanno21609/AdaptiveNeuralTrees
https://github.com/ry/tensorflow-resnet
https://github.com/s9mondal9upriti/Segnet
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/saikrishnadas/ResNet-Pytorch
https://github.com/saloni1998/Cifar-10
https://github.com/sammyamajumdar/ResNet50
https://github.com/sangHa0411/CIFAR100
https://github.com/sangHa0411/ImageNet
https://github.com/sangHa0411/ResNetCIFAR100
https://github.com/sanghyun-son/clustering-kernels
https://github.com/sanoyo/dl-model
https://github.com/satishjasthi/Densenet_smplified
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.