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/ShutoAraki/EverybodyDanceNow-Temporal-FaceGAN
https://github.com/ShuvenduBikash/transformer_spelling_corrector
https://github.com/ShuvenduRoy/FER_TL_PipelineTraining
https://github.com/SiHaoShen/Convolutional-Neural-Networks
https://github.com/SilentFalls/tog
SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color
https://github.com/SimonLliu/CSS_and_up_term
One-shot Face Recognition by Promoting Underrepresented Classes
https://github.com/SimonZsx/nasproj
https://github.com/SiskonEmilia/StyleGAN-PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/SmartEngines/stoppers_modelling
MIDV-2019: Challenges of the modern mobile-based document OCR
https://github.com/SoftwareGift/FeatheNets_Face-Anti-spoofing-Attack-Detection-Challenge-CVPR2019
FeatherNets: Convolutional Neural Networks as Light as Feather for Face Anti-spoofing
https://github.com/SoftwareGift/FeatherNets_Face-Anti-spoofing-Attack-Detection-Challenge-CVPR2019
A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing
https://github.com/SohamSarfare/ADS
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/Soldie/DeOldify-colorir-imagens-antigas
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Soldie/insightface-Rec.Face
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/SongJieLiu/pfld
https://github.com/SonuDileep/3-D-Object-Detection-using-PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/SonyCSLParis/DrumGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Speacer/Super-Resolution-Generative-Adversarial-Networks
https://github.com/SpikeKing/Gaze4Landmarks
https://github.com/Spoorthy-gunda/Image-Classification
https://github.com/StanislasBertrand/RetinaFace-tf2
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/StanislasBertrand/retinaface4j
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/Stephenfang51/Focal_loss_turtorial
https://github.com/StevenBanama/C3AE
C3AE: Exploring the Limits of Compact Model for Age Estimation
https://github.com/Suaro/pidroid
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/Suci2609/generate_train_list.py-
https://github.com/SupratimH/neural-style-transfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Surya9787/suryaprakash
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Sushma07/dancedarknet
https://github.com/SuyashSonawane/fakedetector
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/Swybino/PotatoNet
https://github.com/THHHomas/mls
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/TUM-ML-Lab18/FaceSwap
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Taeuk-Jang/pointcompletion
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Talgin/facerec
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.