https://github.com/paarthneekhara/adversarialdeepfakes
Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples
Papers with Code 아카이브
Facial Recognition and Modelling
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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/pacifinapacific/StyleGAN_LatentEditor
Interpreting the Latent Space of GANs for Semantic Face Editing
https://github.com/paddorch/SelfAttnSent.paddle
https://github.com/papermsucode/2020bboxrestoration
https://github.com/paradocx/LARNet
https://github.com/parthapratimbanik/facial-keypoint-detection-udacity-ppb
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks
https://github.com/parvatijay2901/FaceNet_FR
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/pasrichashivam/hyperface_deep_multi-task-learning_keras_implementation
https://github.com/patelmiteshn/darknet
https://github.com/patrick-batman/Angular-Knowledge-Distillation
ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks
https://github.com/pedrobvidal/insightface
Sample and Computation Redistribution for Efficient Face Detection
https://github.com/peiyunh/tiny
https://github.com/pengrenlai/RetinaNet-tensorflow
https://github.com/pengsongyou/OMG-ADSC
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/penincillin/DREAM
Pose-Robust Face Recognition via Deep Residual Equivariant Mapping
https://github.com/peterhan91/thorax_gan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/petermankowski510/facenet_test
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/peteryuX/arcface-tf2
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/peteryuX/esrgan-tf2
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/peteryuX/retinaface-tf2
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/petrum01/Capstone_project_object_detection
https://github.com/pgtinsley/insightface_oge
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/phamquiluan/ResidualMaskingNetwork
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/phongdinhv/triplet-loss-keras-mnist
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/phuijse/MATIC
https://github.com/piaohe111/gittest
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/pierluigiferrari/ssd_keras
https://github.com/pikabite/segmentations_tf2
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/piotrkawa/audio-deepfake-source-tracing
https://github.com/pipidog/CNLP
https://github.com/playerkk/face-py-faster-rcnn
https://github.com/pocheck-v2/Pocheck-V2-Beta
https://github.com/podgorskiy/StyleGan
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/pohwa065/Deep-Learning-for-Super-Resolution-and-Image-Enhancement
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/pohwa065/SRGAN-for-Super-Resolution-and-Image-Enhancement
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/polarisZhao/PFLD-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.