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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.
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https://github.com/Vivek-23-Titan/Crowd_Detection
Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/ZhengPeng7/SANet-Keras
https://github.com/ZhihengCV/Bayesian-Crowd-Counting
Bayesian Loss for Crowd Count Estimation with Point Supervision
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https://github.com/abuchin/resnet_sign
https://github.com/aby2s/sharpmask
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https://github.com/agassi4013/Log-DenseNet-Tensorflow
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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/akamaster/pytorch_resnet_cifar10
https://github.com/akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101
https://github.com/akhadangi/EM-net
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/akommini/Spoken-Numeric-Digit-detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.