Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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-4/Code11/tree/main/retinaface
Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
https://github.com/2023-MindSpore-4/Code11/tree/main/retinanet_resnet101
https://github.com/2023-MindSpore-4/Code11/tree/main/sphereface
https://github.com/2023-MindSpore-4/Code11/tree/main/ssc_resnet50
https://github.com/2023-MindSpore-4/Code11/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-4/Code2/tree/main/DeepID
https://github.com/2023-MindSpore-4/Code6/tree/main/PyramidBox
PyramidBox++: High Performance Detector for Finding Tiny Face
https://github.com/2023-MindSpore-4/Code6/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code7/tree/main/SRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/2023-MindSpore-4/Code7/tree/main/STPM
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
https://github.com/2023-MindSpore-4/Code7/tree/main/sphereface
https://github.com/2023-MindSpore-4/Code7/tree/main/squeezenet
https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet34
https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-4/Code8/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/2023-MindSpore-4/Code8/tree/main/cct
https://github.com/2023-MindSpore-4/Code8/tree/main/cdp
Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
https://github.com/2023-MindSpore-4/Code8/tree/main/centerface
CenterFace: Joint Face Detection and Alignment Using Face as Point
https://github.com/2023-MindSpore-4/Code8/tree/main/centernet_resnet50_v1
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/2023-MindSpore-4/Code9/tree/main/ResNet
https://github.com/2023-MindSpore-4/Code9/tree/main/RetinaFace_ResNet50
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/2023-MindSpore-4/Code9/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2024-MindSpore-1/Code4/tree/main/Arcface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/2024-MindSpore-1/Code4/tree/main/RetinaFace_ResNet50
https://github.com/2024-MindSpore-1/Code4/tree/main/RetinaNet
https://github.com/2024-MindSpore-1/Code5/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/2024-MindSpore-1/Code5/tree/main/AlignedReID
Domain adaptation for person re-identification on new unlabeled data using AlignedReID++
https://github.com/2024-MindSpore-1/Code7/tree/main/cdp
Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
https://github.com/2024-MindSpore-1/Code7/tree/main/centerface
CenterFace: Joint Face Detection and Alignment Using Face as Point
https://github.com/2024-MindSpore-1/Code7/tree/main/centernet_resnet101
https://github.com/2024-MindSpore-1/Code7/tree/main/centernet_resnet50_v1
https://github.com/2275519762/RetinaFace_Pytorch
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/394781865/insightface
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
https://github.com/3P2S/arcface
https://github.com/497626895/darknet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.