https://github.com/foamliu/Gaze-Estimation
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
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/foamliu/InsightFace-PyTorch
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/foamliu/InsightFace-v2
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/foamliu/InsightFace-v3
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/foamliu/MobileFaceNet
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
https://github.com/foivospar/Arc2Face
https://github.com/foxer9developer/Face-Emotion-to-Emoji-Convertor
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/fpleoni/its_all_in_the_family
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/francislata/Sign-Language-Digits-CNN
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/freddieee/pn_6d_single
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ftdlyc/pointnet_pytorch
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/fulviomascara/pytorch-cv
Facial Expression Recognition Research Based on Deep Learning
https://github.com/fxia22/pointnet.pytorch
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/fznsakib/great-ape-behaviour-detector
https://github.com/gaobb/DLDL-v2
Learning Expectation of Label Distribution for Facial Age and Attractiveness Estimation
https://github.com/gary-kaitung/data-science-portfolio
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/gatheluck/Stronghold
https://github.com/gcastex/PruNet
https://github.com/gcr/torch-residual-networks
https://github.com/genforce/fairgen
Improving the Fairness of Deep Generative Models without Retraining
https://github.com/genforce/ghfeat
https://github.com/genforce/interfacegan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/gengler1123/Triplet_Loss_Demo
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/getcontrol/KYC-tensorflow
https://github.com/getcontrol/KYC-train-model
https://github.com/ghadahamed/darknet
https://github.com/ghaniskn/GCorp-Darknet
https://github.com/ginn24/RefineDet-1
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/github-luffy/PFLD-68points-tensorflow
https://github.com/github-luffy/PFLD_68points_Pytorch
https://github.com/gitlimlab/Representation-Learning-by-Learning-to-Count
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/glarbi/Face-detection
Selective Refinement Network for High Performance Face Detection
https://github.com/glouppe/info8010-deep-learning
https://github.com/gmlunesa/detectfacemask
https://github.com/godofpdog/MobileFaceNet_keras
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/godwinrayanc/YOLOv1-Pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.