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.
https://github.com/vita-epfl/rock-pytorch
https://github.com/vlievin/Unet
https://github.com/voqtuyen/CDCN-Face-Anti-Spoofing.pytorch
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
https://github.com/vwegn/dm
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wangyuan249/Mymmt767
https://github.com/wasilone11/ICPR-RIP-2024
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/waterdisappear/nudt4mstar
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wen227/Pokemon_Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wenxinxu/resnet-in-tensorflow
https://github.com/wenxinxu/resnet_in_tensorflow
https://github.com/wfwf10/feature-based-federated-transfer-learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/winycg/MCL-OKD
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wkostuch/wild-style
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wondonghyeon/protest-detection-violence-estimation
https://github.com/woongjoonchoi/DeepLearningPaper-Reproducing/tree/master/Vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wuqiyao20160118/mini_project-for-CIFAR10
https://github.com/xcmyz/Face-Binary-Classification
https://github.com/xcmyz/FaceDetection
https://github.com/xcmyz/Face_Binary_Classfication
https://github.com/xhlulu/arxiv-assistant
https://github.com/xiaoyufenfei/LEDNet
https://github.com/xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters
https://github.com/xiuyu0000/papers_with_examples/tree/main/cancer_detection_demo
https://github.com/xiuyu0000/tutorials/tree/main/resnet
https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/resnet.py
https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/vgg.py
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/xslidi/EfficientNets_ddl_apex
https://github.com/xufanxiong/classification-of-caltech-256
https://github.com/yahoo/open_nsfw
https://github.com/yakhyo/EfficientNet-PyTorch
https://github.com/yakhyo/gaze-estimation
https://github.com/yakhyo/head-pose-estimation
https://github.com/yakhyo/retinaface-pytorch
https://github.com/yangboz/TransferLearning4Dentist
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/yangorwell/NGPlus
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.