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/MisaOgura/flashtorch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MishaLaskin/vq-vae
https://github.com/MishaLaskin/vqvae
https://github.com/MohamadMerchant/Voice-Authentication-and-Face-Recognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MohamedAbdelsalam9/TT-Transformer
https://github.com/MohdDanish/3D-face-reconstruction
https://github.com/MouxiaoHuang/DUL
https://github.com/MrRiahi/Convolutional-Neural-Networks-Tensorflow
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Mrnoorsingh/QRCode-and-Face-Recognition-for-Access-Control
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Mrzhang3389/FaceRecognition
https://github.com/Mrzhang3389/MTCNN
Real-world adversarial attack on MTCNN face detection system
https://github.com/Mungosin/Mozgalo
https://github.com/N2ITN/Face2Vec
https://github.com/NASA-NeMO-Net/NeMO-Net
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/NJNischal/Facial-Expression-Recognition-with-CNNs
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/NPilis/Facial-Expression-Recognition
https://github.com/NVIDIA/UnsupervisedLandmarkLearning
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/NVIDIA/retinanet-examples
https://github.com/NVlabs/SCOPS
https://github.com/Nacriema/Robust_Face_Recognition
Improving Shadow Suppression for Illumination Robust Face Recognition
https://github.com/Nanway/dfc-vae
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age
https://github.com/NathanHouwaart/EmotionRecognition
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/Natty07/Deep_Learning
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/NeekHua/Pytorch_Retinaface_use_owner_data_test
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/Neilblaze/Adoptic
Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs
https://github.com/Neoanarika/torchexplainer
https://github.com/NetoPedro/VGGFace2-Test
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/NickKaparinos/Google-Landmark-Recognition-2021
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/NikhitaMethwani/Deep-Fakes-Cars-Generation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/NoahBarrett98/ProgressiveGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/NovasMax/R3Det-Refined-Single-Stage-Detector-with-Feature-Refinement-for-RO
https://github.com/Novemser/deep-imitation
https://github.com/NumericalAdvantage/ld-node-facedetector-2
https://github.com/OFRIN/Tensorflow_RetinaFace
https://github.com/OPAYA/Transformer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.