Face Anti-Spoofing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 8
- 보존된 평가 기록
- 31
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/searecluse/cvprw2024
공식 코드https://github.com/sunyiyou/safas
공식 코드Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment
https://github.com/taylover-pei/SSDG-CVPR2020
공식 코드https://github.com/vis-face/cdftn
공식 코드Cyclically Disentangled Feature Translation for Face Anti-spoofing
https://github.com/vis-var/lgsc-for-fas
공식 코드https://github.com/wangzhuo2019/ssan
공식 코드Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofing
https://github.com/wolo-wolo/FSFM
공식 코드https://github.com/xianhua-he/cvpr2024-face-anti-spoofing-challenge
공식 코드Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues
https://github.com/xix-ai/antispoofing
공식 코드Generalizable Method for Face Anti-Spoofing with Semi-Supervised Learning
https://github.com/yaojieliu/CVPR2019-DeepTreeLearningForZeroShotFaceAntispoofing
공식 코드https://github.com/yaojieliu/ECCV20-STDN
공식 코드https://github.com/yaojieliu/ECCV2018-FaceDeSpoofing
공식 코드https://github.com/yjyddq/DLIF
공식 코드https://github.com/zitongyu/flex-modal-fas
공식 코드https://github.com/2023-MindSpore-1/ms-code-177
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/lresnet100e_ir
https://github.com/2023-MindSpore-1/ms-code-201
https://github.com/2023-MindSpore-1/ms-code-208
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceAttribute
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnet50_adv_pruning
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet34
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-1/ms-code-22
https://github.com/2023-MindSpore-1/ms-code-49
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code-5/tree/main/lresnet100e_ir
https://github.com/2023-MindSpore-4/Code10/tree/main/ResNet
https://github.com/2023-MindSpore-4/Code10/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code11/tree/main/resnet50_adv_pruning
https://github.com/2023-MindSpore-4/Code11/tree/main/ssc_resnet50
https://github.com/2023-MindSpore-4/Code11/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-4/Code6/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code7/tree/main/STPM
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet34
https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet_34
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.