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/mundanePeo/faceRecognition
https://github.com/mushfiqurrahman250/Face-Recognition-master
https://github.com/musifahamran/FYP
https://github.com/musikisomorphie/swd
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/muzairkhattak/multimodal-prompt-learning
https://github.com/muzairkhattak/protext
https://github.com/nabarunbaruaAIML/ATCC_Yolov5
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/nagadomi/kaggle-cifar10-torch7
https://github.com/namdvt/Focal-loss-pytorch-implementation
https://github.com/nannau/DoWnGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/nanzhaogang/contrib/tree/master/application/circle-loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/nashory/pggan-pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/natel9178/transformer-refork
https://github.com/naver-ai/StyleMapGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/naykun/tf_pg_gans
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/ndb796/pytorch-adversarial-training-cifar
https://github.com/nddoshi/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/neelabh17/MAVI-Face
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/neerajvashistha/vgg16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/negarhdr/skeleton-based-action-recognition
https://github.com/nelson-mig-l/boofcv-dithering
https://github.com/neshitov/UNet
https://github.com/neuralet/facemask
https://github.com/neverUseThisName/Decorrelated-Adversarial-Learning
Decorrelated Adversarial Learning for Age-Invariant Face Recognition
https://github.com/neverUseThisName/Face-X-Ray
https://github.com/ngonthier/multiresolution_texture
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nguoido/Yolo-alexeyAB
https://github.com/nhanvu39/ArcFace
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/nhatduy19599/insightface-master
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/nicaogr/multiresolution_texture
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nicku-a/Weather_Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nicolalandro/Padam
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nidolow/image-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nii-yamagishilab/ClassNSeg
Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
https://github.com/nikitakaraevv/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.