Papers with Code 아카이브
Face Reconstruction
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Face reconstruction is the task of recovering the facial geometry of a face from an image.
<span style="color:grey; opacity: 0.6">( Image credit: Microsoft Deep3DFaceReconstruction )</span>
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.