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/anjandeepsahni/face_recognition
https://github.com/anjith2006/bob.paper.mcae.icb2019
Domain Adaptation in Multi-Channel Autoencoder based Features for Robust Face Anti-Spoofing
https://github.com/anjith2006/bob.paper.mccnn.tifs2018
Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network
https://github.com/anjith2006/bob.paper.oneclass_mccnn_2019
https://github.com/anjith2006/bob.paper.tbiom2023_edgeface
https://github.com/anjith2006/bob.paper.tifs2022_hfr_prepended_domain_transformer
Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles
https://github.com/ankit-vaghela30/Google-landmark-prediction
https://github.com/annabellachen/newDarknet
https://github.com/anookeen/yolo
https://github.com/anoushkrit/Knowledge
https://github.com/anshky/HR-NET
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/anshu123priya/Real-v-s-Fake-Emotion-Challenge
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/anshu123priya/Real-vs-Fake-Emotion-Challenge
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/anuj-anuj/face-similarity
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/anujdutt9/Artistic-Style-Transfer-using-Keras-Tensorflow
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/aobaruwa/TensorFlow-Projects
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/aoru45/BasketNet
https://github.com/aoru45/Deep-Anomaly-Detection-for-Generalized-Face-Anti-Spoofing
https://github.com/aoru45/LFFD-Pytorch
https://github.com/apaz-cli/ML-ImageHash
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/apisarek/gan_advances
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/aporw/Class-Attendance-Tool--Face-Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/arahosu/musicslots
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/aralhekimoglu/face
Sample and Computation Redistribution for Efficient Face Detection
https://github.com/arghadeep25/Face-Detection
https://github.com/ariangc/breinchallenge
https://github.com/ariel415el/ALAE
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/ariel415el/SimplePytorch-ALAE
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/arkel23/Danbooru2018AnimeCharacterRecognitionDataset_Revamped
https://github.com/arsfutura/face-recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/artemmavrin/focal-loss
https://github.com/arturjordao/arturjordao
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction Method
https://github.com/artxtech/darknet-rnn
https://github.com/artynet/darknet-alexeyAB
https://github.com/ashawkey/RAD-NeRF
Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.