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/kishansharma3012/Deep_Head_Pose_Estimation
https://github.com/kishorkuttan/traffic_net
https://github.com/kitliu5/Stanford-CS236-Project
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/kkelchte/task_free_continual_learning
https://github.com/km1414/CNN-models
https://github.com/kmohanku/Low-Light-Image-Video-Enhancement
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/kmzzhang/nbi
https://github.com/kongzhiyou/darknet-master
https://github.com/konny0311/vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/konstantinos-p/image_classification_SOTA
https://github.com/kooBH/facenet_verification
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/kornia/kornia
https://github.com/koshian2/ResNet-MultipleFramework
https://github.com/koshian2/swd-pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/krantirk/Face-detection-and-counting-
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/krantirk/Self-Supervised-photo
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/kreimanlab/HumanIntentionInferenceZeroShot
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/krishnakarthi/COVID-19_Prediction
https://github.com/ktjonsson/keras-ArcFace
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/kuaikuaikim/DFace
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/kuangliu/pytorch-fpn
https://github.com/kukby/Mish-semantic-segmentation-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/kukico/learning
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/kumarnikhil936/Facial-Emotion-Recognition
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/kun-woo-park/Deeplearning_project_STL_10
https://github.com/kvijaykrish/Bosch_AI_VehicleClassification
https://github.com/kwantommy/fgvc6-kaggle-cassava-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/kwotsin/TensorFlow-ENet
https://github.com/kyle-dorman/bayesian-neural-network-blogpost
https://github.com/kynkaat/improved-precision-and-recall-metric
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/kyranstar/Narcissus
https://github.com/kyunghwan/darknet_v3
https://github.com/kzmttr/UMDFA
https://github.com/lab-midas/med_segmentation
https://github.com/labmlai/annotated_deep_learning_paper_implementations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.