https://github.com/akanimax/T2F
Progressive Growing of GANs for Improved Quality, Stability, and Variation
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/akanimax/pro_gan_pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/akhadangi/EM-net
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/akirafukui/vqa-mcb
https://github.com/akommini/Spoken-Numeric-Digit-detection
https://github.com/akshaybahadur21/Facial-Recognition-using-Facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/akshayraghavan21/Face_Recognition_Using_Facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/alalagong/LEDNet
https://github.com/albanie/mcnCrossModalEmotions
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/albertomontesg/keras-model-zoo
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/alecwangcq/KFAC-Pytorch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/alex-f1tor/Image-Caption
https://github.com/alexattia/ExtendedTinyFaces
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/alexeyhorkin/ProGAN-PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/alexsax/midlevel-reps
https://github.com/alexwdong/IncubatorCVProject
https://github.com/alfagao/DeOldify
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/ali-vilab/FlashFace
FlashFace: Human Image Personalization with High-fidelity Identity Preservation
https://github.com/alibaba/EasyCV
https://github.com/alililia/ascend_ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/alililia/ascend_FaceAttribute
https://github.com/alililia/ascend_HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/alililia/ascend_SE-Net
https://github.com/alililia/ascend_sphereface
https://github.com/alililia/gpu_sphereface
https://github.com/alililia/ms_contrib/tree/main/ascend_vgg19
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/alililia/ms_contrib/tree/main/gpu_vgg19
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/alililia/ms_extend/tree/main/gpu_resnet
https://github.com/alililia/ms_extend/tree/main/gpu_retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/alinlab/LfF
Learning from Failure: Training Debiased Classifier from Biased Classifier
https://github.com/aliprf/Ad-Corre
https://github.com/alisha17/benchmarks
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/alldbi/Factorized-Spatial-Embeddings
Unsupervised learning of object landmarks by factorized spatial embeddings
https://github.com/allenai/satlas-super-resolution
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/alrojo/lasagne_residual_network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.