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/carlosb1/upc-aidl-19-team4
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/carolgithubv1/convnets-keras
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/chayanchatterjee/cbc-skynet
https://github.com/chayanchatterjee/gw-skylocator
https://github.com/chldydgh4687/2020-1.VideoCaptioning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/chosj95/PFPNet.pytorch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/chrhenning/hypercl
https://github.com/cj-mclaughlin/segmentation_research
https://github.com/cjfghk5697/Pytorch-Research-Paper-Implementations
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/clvrai/representation-learning-by-learning-to-count
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/cocopambag/ResNet
https://github.com/code-implementation1/Code3/tree/main/FaceAttribute
https://github.com/code-implementation1/Code5/tree/main/lresnet100e_ir
https://github.com/code-implementation1/Code7/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/code-implementation1/Code7/tree/main/resnetv2
https://github.com/code-implementation1/Code9/tree/main/vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/coderwangson/Face-anti-spoofing-based-on-color-texture-analysis
https://github.com/coderwangson/Learn-Convolutional-Neural-Network-for-Face-Anti-Spoofing_pytorch
https://github.com/cornell-zhang/allo-pldi24-artifact
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/cryu854/ArbitraryStyle
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/cryu854/ArbitraryStyle-tfjs
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/daimonae/Fundus-Image-Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/danielamassiceti/CCA-visualdialogue
https://github.com/danielparada1/RL_SpaceInvaders
https://github.com/darrishabh/coviprox
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datawiz1984/MLND_Capstone_Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datawiz1984/malaria-model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/datoboat/Vehicle-Detection
https://github.com/dead-mazai/avia-missing-airplanes
https://github.com/deepmind/dm-haiku
https://github.com/deepmodeling/deepmd-kit
https://github.com/deepquestai/fire-smoke-dataset
https://github.com/demul/ResidualNet
https://github.com/deontaepharr/Residual-Attention-Network
https://github.com/dishen12/py03
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.