Papers with Code 아카이브
Face Verification
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Face Verification is a machine learning task in computer vision that involves determining whether two facial images belong to the same person or not. The task involves extracting features from the facial images, such as the shape and texture of the face, and then using these features to compare and verify the similarity between the images.
<span style="color:grey; opacity: 0.6">( Image credit: Pose-Robust Face Recognition via Deep Residual Equivariant Mapping )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nanzhaogang/contrib/tree/master/application/circle-loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/neelabh17/MAVI-Face
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/neshitov/UNet
https://github.com/nguoido/Yolo-alexeyAB
https://github.com/nhanvu39/ArcFace
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/nhatduy19599/insightface-master
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/niuxiaozhang/mxnet-retinaface-to-gluon
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/njordsir/Clustering-Faces
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/notecola/facenet-light
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/nova26/facePoseEstimation
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/opencv/opencv_zoo/tree/master/models/face_recognition_sface
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
https://github.com/ozora-ogino/LCNN
https://github.com/p0werweirdo/tagfcl
Compacting, Picking and Growing for Unforgetting Continual Learning
https://github.com/parvatijay2901/FaceNet_FR
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/patelmiteshn/darknet
https://github.com/pedrobvidal/insightface
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/peteryuX/retinaface-tf2
RetinaFace: Single-stage Dense Face Localisation in the Wild
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/piaohe111/gittest
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/pierluigiferrari/ssd_keras
https://github.com/ppokhare/Handling-Imbalanced-Dataset-for-classification-task
https://github.com/ppriyank/Pytorch-Additive_Margin_Softmax_for_Face_Verification
https://github.com/prajinkhadka/face_det_check
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/pranavjadhav001/arcface_inversion
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.