Papers with Code 아카이브
Face Identification
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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/nveldt/LamCC
https://github.com/obj2vec/obj2vec
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/oktapodi/ps_resNet
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/omron-sinicx/sbsfigures
PetFace: A Large-Scale Dataset and Benchmark for Animal Identification
https://github.com/oorrppp2/darknet-pose
https://github.com/open-mmlab/mmdetection
https://github.com/ozora-ogino/LCNN
https://github.com/parvatijay2901/FaceNet_FR
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/patelmiteshn/darknet
https://github.com/pengrenlai/RetinaNet-tensorflow
https://github.com/penincillin/DREAM
Pose-Robust Face Recognition via Deep Residual Equivariant Mapping
https://github.com/petermankowski510/facenet_test
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/peteryuX/arcface-tf2
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/petrum01/Capstone_project_object_detection
https://github.com/pgtinsley/insightface_oge
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/phongdinhv/triplet-loss-keras-mnist
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/phuijse/MATIC
https://github.com/pierluigiferrari/ssd_keras
https://github.com/pipidog/CNLP
https://github.com/ppokhare/Handling-Imbalanced-Dataset-for-classification-task
https://github.com/ppriyank/Pytorch-Additive_Margin_Softmax_for_Face_Verification
https://github.com/pranavjadhav001/arcface_inversion
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/pytorch/vision
https://github.com/qbxlvnf11/face-detection-MTCNN
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/qingyujean/Classification-on-imbalanced-data
https://github.com/quangson05dt1/keras_facenet_ver1
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/rahowa/catboost_focal_loss
https://github.com/rainofmine/Face_Attention_Network
https://github.com/rap-music/-
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/raspstephan/sugar-flower-fish-or-gravel
https://github.com/rebeccagio/object_detection
https://github.com/reneang17/authorencoder
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/richaagrawa/Facial-Recognition-System
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/richmondu/libfaceid
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/rikichou/face_recognition_insight_face
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.