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Pedestrian Attribute Recognition

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하위 태스크: 0
평가표: 8
보존된 평가 기록: 30

Pedestrian attribution recognition is the task of recognizing pedestrian features - such as whether they are talking on a phone, whether they have a backpack, and so on.

<span style="color:grey; opacity: 0.6">( Image credit: HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis )</span>

코드

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

https://github.com/nicolalandro/Padam

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https://github.com/niranjana98/Image-Classification

Densely Connected Convolutional Networks

https://github.com/noahfl/densenet-sdr

Densely Connected Convolutional Networks

https://github.com/northeastsquare/effficientnet

Deep Residual Learning for Image Recognition

https://github.com/nsom/Basic-Models

Deep Residual Learning for Image Recognition

https://github.com/nsom/VGG16

Deep Residual Learning for Image Recognition

https://github.com/ntrin/CIFAR_10_ML

Deep Residual Learning for Image Recognition

https://github.com/okason97/DenseNet-Tensorflow2

Densely Connected Convolutional Networks

https://github.com/okason97/handshape-recognition

Densely Connected Convolutional Networks

https://github.com/ollewelin/libtorch-GPU-CNN-test-MNIST-with-Batchnorm

Deep Residual Learning for Image Recognition

https://github.com/open-mmlab/mmclassification

Deep Residual Learning for Image Recognition

https://github.com/open-mmlab/mmpose

Deep Residual Learning for Image Recognition

https://github.com/oskyhn/CNNs-Without-Borders

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https://github.com/osmr/imgclsmob

Deep Residual Learning for Image Recognition

https://github.com/oxygen0605/ImageClassification

Deep Residual Learning for Image Recognition

https://github.com/p-mc-grath/DMMFODS

Densely Connected Convolutional Networks

https://github.com/pacharadanait/Densnet_project

Densely Connected Convolutional Networks

https://github.com/paperswithcode/paperswithcode-client

Deep Residual Learning for Image Recognition

https://github.com/parviagrawal/IdenProf

Deep Residual Learning for Image Recognition

https://github.com/patientzero/timage-icann2019

Deep Residual Learning for Image Recognition

https://github.com/paulblum00/ResNet-Recreation

Deep Residual Learning for Image Recognition

https://github.com/pawelbeza/ClothesDetectorModel

Deep Residual Learning for Image Recognition

https://github.com/peteryuX/arcface-tf2

Deep Residual Learning for Image Recognition

https://github.com/phillity/BioCapsule

Deep Residual Learning for Image Recognition

https://github.com/pikkaay/efficientnet_gpu

Deep Residual Learning for Image Recognition

https://github.com/pmcgrath249/DMMFODS

Densely Connected Convolutional Networks

https://github.com/pmcgrath249/DeepCVLab

Densely Connected Convolutional Networks

https://github.com/pmcgrath249/DeepCV_Lab

Densely Connected Convolutional Networks

https://github.com/priyankadeybhadra/CNN-on-CIFR

Densely Connected Convolutional Networks

https://github.com/priyavrat-misra/xrays-and-gradcam

Deep Residual Learning for Image Recognition

https://github.com/pszemraj/BoulderAreaDetector

Deep Residual Learning for Image Recognition

https://github.com/pudae/tensorflow-densenet

Densely Connected Convolutional Networks

https://github.com/pyaf/DenseNet-MURA-PyTorch

Densely Connected Convolutional Networks

https://github.com/pytorch/vision

Deep Residual Learning for Image Recognition

https://github.com/pytorch/vision/blob/main/torchvision/models/densenet.py

Densely Connected Convolutional Networks

https://github.com/qubvel/efficientnet

Deep Residual Learning for Image Recognition

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