Papers with Code 아카이브
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/DrRyanHuang/VGGNet
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Duplums/bhb10k-dl-benchmark
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EiroaMD/final_project_IH_pneumonia
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EngineeringSapien/NarutoCV
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EricAlcaide/MiniFold
https://github.com/EstherBear/implementation-of-pruning-filters
https://github.com/EverLookNeverSee/diag2model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EvgenyVendrov/DeepLearningCourse
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/FaceOnLive/Face-Liveness-Detection-SDK-Android
https://github.com/FaceOnLive/Face-Liveness-Detection-SDK-Linux
https://github.com/FrancescoSaverioZuppichini/ResNet
https://github.com/GKalliatakis/Keras-VGG16-places365
https://github.com/GabrieleMonte/CoMBInE
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Glp91/fire-detection
https://github.com/Godot-yry/VGG16_mindspore
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Gojay001/toolkit-DeepLearning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Graylab/deepH3-distances-orientations
https://github.com/HHTseng/video-classification
https://github.com/Halesu/4th-ML100Days
https://github.com/HarmanDotpy/Normalizations-in-Deep-Learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Harry-Muzart/harry-muzart.github.io
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Hazqeel09/ellzaf_ml
S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens
https://github.com/IBM/NeuronAlignment
https://github.com/IMvision12/keras-vision-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/JContro/pytorch_projects
https://github.com/JHLee0513/Salt_detection_challenge
https://github.com/JONGSKY/paper
https://github.com/JaidedAI/EasyOCR
https://github.com/James-Gilbert-/medical-deep-learning
https://github.com/James-Gilbert-/pneumonia-detection
https://github.com/JanMarcelKezmann/Residual-Network-Architectures
https://github.com/JayPatwardhan/ResNet-PyTorch
https://github.com/JeansonYang/VGG16-MindSpore
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.