Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceAttribute
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceDetection
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-214/tree/main/HMR
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/PGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/PyramidBox
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnet50_adv_pruning
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-217/tree/main/ssd_resnet34
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-1/ms-code-22
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/RetinaFace_ResNet50
Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/RetinaNet
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/2023-MindSpore-1/ms-code-44
https://github.com/2023-MindSpore-1/ms-code-49
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/centerface
CenterFace: Joint Face Detection and Alignment Using Face as Point
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/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-4/Code-5/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/2023-MindSpore-4/Code-5/tree/main/LightCNN
https://github.com/2023-MindSpore-4/Code-5/tree/main/MaskedFaceRecognition
https://github.com/2023-MindSpore-4/Code-5/tree/main/lresnet100e_ir
https://github.com/2023-MindSpore-4/Code1/tree/main/Arcface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/2023-MindSpore-4/Code10/tree/main/Arcface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/2023-MindSpore-4/Code10/tree/main/ResNet
https://github.com/2023-MindSpore-4/Code10/tree/main/RetinaFace_ResNet50
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/2023-MindSpore-4/Code10/tree/main/RetinaNet
https://github.com/2023-MindSpore-4/Code10/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code11/tree/main/SRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.