https://github.com/pvskand/DisguiseNet
공식 코드DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild
Papers with Code 아카이브
Face Verification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/qizhangli/nobox-attacks
공식 코드https://github.com/ryanhe312/LatentFace
공식 코드A Generative Framework for Self-Supervised Facial Representation Learning
https://github.com/sam575/axial-gan
공식 코드https://github.com/sciencefans/Quality-Aware-Network
공식 코드https://github.com/seasonSH/Probabilistic-Face-Embeddings
공식 코드https://github.com/seymayucer/facialphenotypes
공식 코드Measuring Hidden Bias within Face Recognition via Racial Phenotypes
https://github.com/storymy/take-off-eyeglasses
공식 코드Portrait Eyeglasses and Shadow Removal by Leveraging 3D Synthetic Data
https://github.com/tfwu/FaceDetection-ConvNet-3D
공식 코드Face Detection with End-to-End Integration of a ConvNet and a 3D Model
https://github.com/tiandunx/FFC
공식 코드An Efficient Training Approach for Very Large Scale Face Recognition
https://github.com/tinkoff-ai/probabilistic-embeddings
공식 코드https://github.com/vuvko/fitw2020
공식 코드Achieving Better Kinship Recognition Through Better Baseline
https://github.com/wy1iu/sphereface
공식 코드https://github.com/wznpub/MMA_Regularization
공식 코드MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles
https://github.com/xf1994/ECML
공식 코드ECML: An Ensemble Cascade Metric Learning Mechanism towards Face Verification
https://github.com/xiaoboCASIA/SV-X-Softmax
공식 코드https://github.com/ydc123/Dark_Surrogate_Model
공식 코드Boosting the Adversarial Transferability of Surrogate Models with Dark Knowledge
https://github.com/zhongyy/SFace
공식 코드SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
https://github.com/zma-c-137/VarGFaceNet
공식 코드https://gitlab.com/pl8787/CaffeAttention
공식 코드https://dagshub.com/Bharat-mtr/LightCNN
https://github.com/18alantom/identify
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/18alantom/smel_project
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/1996scarlet/ArcFace-Multiplex-Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/1996scarlet/Laser-Eye
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/1996scarlet/faster-mobile-retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/2023-MindSpore-1/ms-code-178
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/LightCNN
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/DeepID
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceNet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/retinanet_resnet101
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/retinanet_resnet152
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/RetinaNet
https://github.com/2023-MindSpore-1/ms-code-44
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/centernet_resnet50_v1
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/2023-MindSpore-4/Code-5/tree/main/LightCNN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.