Papers with Code 아카이브
Face Identification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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Face identification is the task of matching a given face image to one in an existing database of faces. It is the second part of face recognition (the first part being detection). It is a one-to-many mapping: you have to find an unknown person in a database to find who that person is.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Maskify/darknet
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Network_In_Network
https://github.com/MegEngine/Models/tree/master/official/vision/detection
https://github.com/Mind23-2/MindCode-101/tree/main/LightCNN
https://github.com/Mind23-2/MindCode-13
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/Mind23-2/MindCode-176
https://github.com/Mind23-2/MindCode-3/tree/main/LightCNN
https://github.com/Mind23-2/MindCode-56
https://github.com/Mind23-2/MindCode-70
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Mind23-2/MindCode-95
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/MindSpore-paper-code-3/code2/tree/main/DeepID
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceRecognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet101
https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet152
https://github.com/MindSpore-paper-code-3/code7/tree/main/FaceRecognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MindSpore-paper-code-3/code8/tree/main/DeepID
https://github.com/MindSpore-paper-code-3/code8/tree/main/faceboxes
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MindSpore-scientific-2/code-11/tree/main/SV-X-Softmax
https://github.com/MohamadMerchant/Voice-Authentication-and-Face-Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Mrnoorsingh/QRCode-and-Face-Recognition-for-Access-Control
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Mrzhang3389/FaceRecognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/NVIDIA/retinanet-examples
https://github.com/Natty07/Deep_Learning
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/NickKaparinos/Google-Landmark-Recognition-2021
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/NovasMax/R3Det-Refined-Single-Stage-Detector-with-Feature-Refinement-for-RO
https://github.com/OFRIN/Tensorflow_RetinaFace
https://github.com/PaddlePaddle/PLSC
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/PaddlePaddle/PaddleClas
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/PolarisAlpha/darknet
https://github.com/Popoooo/darknet_test
https://github.com/Porechniy13/FaceReco
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/PowerOfDream/digitx
https://github.com/Prateek93a/DoodleAI
https://github.com/PushpakBhoge/Face_Recognition_TF
FaceNet: A Unified Embedding for Face Recognition and Clustering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.