Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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/facebook/fb.resnet.torch
https://github.com/facebookarchive/fb.resnet.torch
https://github.com/facebookresearch/DomainBed
https://github.com/facebookresearch/detectron2
https://github.com/facebookresearch/disentangling-correlated-factors
https://github.com/facebookresearch/hiera
https://github.com/facebookresearch/pycls
https://github.com/facebookresearch/pytext
https://github.com/facebookresearch/pytorch_GAN_zoo
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/facebookresearch/stochastic_gradient_push
https://github.com/facebookresearch/supervision-by-registration
https://github.com/facundoq/transformational_measures_experiments
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/faddey-w/face-swap
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/fangzong12/FeatherNet
FeatherNets: Convolutional Neural Networks as Light as Feather for Face Anti-spoofing
https://github.com/faridSam/srn
Selective Refinement Network for High Performance Face Detection
https://github.com/farinamatteo/zero
https://github.com/fastai/fastai
https://github.com/fbplab/MEBeauty-database
https://github.com/fchollet/deep-learning-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/feidfoe/AdjustBnd4Imbalance
https://github.com/feiyunzhang/person_attribute_mxnet
MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes
https://github.com/felipeyanez/nmf
Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence
https://github.com/felixgwu/img_classification_pk_pytorch
https://github.com/fenghansen/ESRGAN-Keras
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/fenglian425/Agriculture_AI
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/fengredrum/cnn-xla
https://github.com/ffletcherr/face-recognition-liveness
Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
https://github.com/ffr4nz/UnknownUnknowns
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/final-0/Real-ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/final-0/Real-ESRGAN-bicubic
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/fizyr/keras-retinanet
https://github.com/flora-zyx/SJNet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/flynn-chen/faceforensics_benchmark
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/flytocc/PaddleClas
https://github.com/fnyanez/nmf
Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.