https://github.com/SeungyounShin/EXTD
EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
Papers with Code 아카이브
3D Face Reconstruction
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/SeungyounShin/GroupFace
GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition
https://github.com/SevenZhan/Pytorch
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/SforAiDl/KD_Lib
https://github.com/ShadowShadowWong/update-pointnet-work
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/ShaharrHorn/Detection-Game-logic
https://github.com/ShaojieJiang/tldr
https://github.com/ShawnDing1994/AOFP
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
https://github.com/ShenYujun/InterFaceGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/ShiqiYu/libfacedetection
https://github.com/Shraddha2013/customyolo
https://github.com/Shraddha2013/darknett
https://github.com/Shraddha2013/darknetyol
https://github.com/Shraddha2013/darknetyolo
https://github.com/Shraddha2013/darknetyolo3
https://github.com/Shraddha2013/mydarknetyolo
https://github.com/Shraddha2013/myfileyolo
https://github.com/ShutoAraki/EverybodyDanceNow-Temporal-FaceGAN
https://github.com/ShuvenduBikash/transformer_spelling_corrector
https://github.com/ShuvenduRoy/FER_TL_PipelineTraining
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/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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.