Face Anti-Spoofing
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Facial anti-spoofing is the task of preventing false facial verification by using a photo, video, mask or a different substitute for an authorized person’s face. Some examples of attacks:
Print attack: The attacker uses someone’s photo. The image is printed or displayed on a digital device.
Replay/video attack: A more sophisticated way to trick the system, which usually requires a looped video of a victim’s face. This approach ensures behaviour and facial movements to look more ‘natural’ compared to holding someone’s photo.
3D mask attack: During this type of attack, a mask is used as the tool of choice for spoofing. It’s an even more sophisticated attack than playing a face video. In addition to natural facial movements, it enables ways to deceive some extra layers of protection such as depth sensors.
<span style="color:grey; opacity: 0.6">( Image credit: Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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https://github.com/mahmoodlab/hest
https://github.com/makatx/YOLO_ResNet
https://github.com/malin9402/2020-0221
https://github.com/manankshastri/ART
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https://github.com/manoranjan03/PaperImplementations
https://github.com/marload/ConvNets-TensorFlow2
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https://github.com/masoudnick/brain-tumor-mri-classification
https://github.com/matakshay/Neural_Image_Caption_Generator
https://github.com/maxwelltsai/DeepGalaxy
https://github.com/mbsariyildiz/resnet-pytorch
https://github.com/mdda/deep-learning-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/megvii-research/basecls/tree/main/zoo/public/resnet
https://github.com/megvii-research/basecls/tree/main/zoo/public/vgg
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https://github.com/mgonzalezrivero/reef_learning
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https://github.com/microsoft/fb.resnet.torch
https://github.com/mikekestemont/deepscript
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindlab-ai/mindcv/blob/main/examples/train_cifar_dynamic.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/resnet.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/vgg.py
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet50_quant
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet_thor
https://github.com/mindspore-ai/models/tree/master/official/cv/vgg16
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https://github.com/mindspore-ai/models/tree/master/research/cv/FaceAttribute
https://github.com/mindspore-ai/models/tree/master/research/cv/vgg19
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/backbone/resnet.py
https://github.com/mindspore-courses/MindSpore-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-courses/heads-on-mindspore/tree/main/1-best-practice/models
https://github.com/mindspore-ecosystem/mindcv/blob/main/mindcv/models/resnet.py
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