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/shoaibahmed/CrossLayerPooling
https://github.com/shoji9x9/CIFAR-10-By-small-ResNet
https://github.com/shoji9x9/Fashion-MNIST-By-ResNet
https://github.com/shoutOutYangJie/Few-Shot-Adversarial-Learning-for-face-swap
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
https://github.com/shridharrhegde/vgg-age
Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model
https://github.com/shtnkgm/VisionFrameworkSample
https://github.com/shuShelby/main
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/shuliyao/GANimation_TL
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/shuuchen/HRNet
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/shyhyawJou/ArcFace-Pytorch
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/sibozhang/Text2Video
https://github.com/sicxu/Deep3DFaceRecon_pytorch
https://github.com/siddharthbhonge/Neural_Style_transfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/sidify/resnet_focal_loss
https://github.com/sidward14/gan-lab
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/sijinkim/pggan-clone
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/simo-bat/Crack_detection
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/simon20010923/DDAMFN
https://github.com/simonjisu/nsmc_study
https://github.com/simonlevine/11785-project
https://github.com/simonlevine/clinical-longformer
https://github.com/sims-s/bird-gan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/singh-shakti94/Deep-Learning-Project
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/siqueira-hc/Efficient-Facial-Feature-Learning-with-Wide-Ensemble-based-Convolutional-Neural-Networks
Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks
https://github.com/sitegui/ceci-nest-pas-un-chat
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/sithu31296/EasyFace
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/sithu31296/pose-estimation
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/skbadhsm/darknet2
https://github.com/skkuse02/2019fall_41class_team8
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/skymanaditya1/FaceOff
https://github.com/slawekslex/ArcFace_Explained
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/smc-x/ms-resnetv2
https://github.com/smhall97/deep_dreaming_music
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/smkim7-kr/toy-projects/tree/master/ArcFace-visualization
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/smu-ivpl/DeepfakeDetection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.