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/code-implementation1/Code9/tree/main/vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/code-kage/facenet_mini
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/code-trip/insightface-mxnet
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/coderwangson/Face-anti-spoofing-based-on-color-texture-analysis
https://github.com/coderwangson/Learn-Convolutional-Neural-Network-for-Face-Anti-Spoofing_pytorch
https://github.com/comratvlad/sv_softmax
https://github.com/convergencelab/ProgressiveGAN-SR
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/cornell-zhang/allo-pldi24-artifact
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/coronnie/HouseGuard
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/crishy1995/headnerf
https://github.com/cryu854/ArbitraryStyle
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/cryu854/ArbitraryStyle-tfjs
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/cs-giung/FSRNet-pytorch
FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors
https://github.com/csm-kr/Retinanet_pytorch
https://github.com/cuguilke/microexpnet
MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Face Images
https://github.com/cuiziteng/iccv_maet
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/cuiziteng/maet
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/cviaai/PSF-GAN-ESTIMATION
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/cvqluu/Additive-Margin-Softmax-Loss-Pytorch
https://github.com/cvqluu/Angular-Penalty-Softmax-Losses-Pytorch
https://github.com/cvtower/SeesawNet-pytorch-reimplement
SeesawFaceNets: sparse and robust face verification model for mobile platform
https://github.com/cvtower/SeesawNet_pytorch
SeesawFaceNets: sparse and robust face verification model for mobile platform
https://github.com/cvtower/seesawfacenet_pytorch
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
https://github.com/cydonia999/Tiny_Faces_in_Tensorflow
https://github.com/cydonia999/VGGFace2-pytorch
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/d-shivam/Pose-estimation-based-action-recognition-for-help-Situation-Identification
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/daimonae/Fundus-Image-Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/dakenan1/Everybody-Dance-Now
https://github.com/dalisson/am_softmax
https://github.com/danielamassiceti/CCA-visualdialogue
https://github.com/danielparada1/RL_SpaceInvaders
https://github.com/danmohaha/CVPRW2019_Face_Artifacts
Exposing DeepFake Videos By Detecting Face Warping Artifacts
https://github.com/danmohaha/WIFS2018_In_Ictu_Oculi
In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye Blinking
https://github.com/darkAlert/retinafacert
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/darrishabh/coviprox
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.