Papers with Code 아카이브
Age-Invariant Face Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Age-invariant face recognition is the task of performing face recognition that is invariant to differences in age.
<span style="color:grey; opacity: 0.6">( Image credit: Look Across Elapse )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AlfredXiangWu/face_verification_experiment
공식 코드https://github.com/FaceOnLive/Face-Recognition-SDK-Android
공식 코드Cross-Age Contrastive Learning for Age-Invariant Face Recognition
https://github.com/Hzzone/MTLFace
공식 코드When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
https://github.com/ZhaoJ9014/High_Performance_Face_Recognition
공식 코드https://github.com/zhaoyuzhi/childpredictor
공식 코드ChildPredictor: A Child Face Prediction Framework with Disentangled Learning
https://dagshub.com/Bharat-mtr/LightCNN
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/LightCNN
https://github.com/2023-MindSpore-4/Code-5/tree/main/LightCNN
https://github.com/Asthestarsfalll/LightCNN-MegEngine
https://github.com/Faceplugin-ltd/FaceRecognition-Android
https://github.com/Mind23-2/MindCode-101/tree/main/LightCNN
https://github.com/Mind23-2/MindCode-3/tree/main/LightCNN
https://github.com/Mind23-2/MindCode-56
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
https://github.com/Recognito-Vision/Face-SDK-Linux-Demos
Cross-Age Contrastive Learning for Age-Invariant Face Recognition
https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
https://github.com/code-implementation1/Code4/tree/main/LightCNN
https://github.com/gcastex/PruNet
https://github.com/lyatdawn/lightcnn-mxnet
https://github.com/mindspore-ai/models/blob/master/research/cv/LightCNN/
https://github.com/neverUseThisName/Decorrelated-Adversarial-Learning
Decorrelated Adversarial Learning for Age-Invariant Face Recognition
https://github.com/ozora-ogino/LCNN
https://github.com/yxu0611/tensorflow-implementation-of-lcnn
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.