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/mundanePeo/faceRecognition
https://github.com/mushfiqurrahman250/Face-Recognition-master
https://github.com/musifahamran/FYP
https://github.com/musikisomorphie/swd
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/muzairkhattak/multimodal-prompt-learning
https://github.com/muzairkhattak/protext
https://github.com/nabarunbaruaAIML/ATCC_Yolov5
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/nagadomi/kaggle-cifar10-torch7
https://github.com/namdvt/Focal-loss-pytorch-implementation
https://github.com/nannau/DoWnGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/nanzhaogang/contrib/tree/master/application/circle-loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/nashory/pggan-pytorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/natel9178/transformer-refork
https://github.com/naver-ai/StyleMapGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/naykun/tf_pg_gans
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/ndb796/pytorch-adversarial-training-cifar
https://github.com/nddoshi/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/neelabh17/MAVI-Face
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/neerajvashistha/vgg16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/negarhdr/skeleton-based-action-recognition
https://github.com/nelson-mig-l/boofcv-dithering
https://github.com/neshitov/UNet
https://github.com/neuralet/facemask
https://github.com/neverUseThisName/Decorrelated-Adversarial-Learning
Decorrelated Adversarial Learning for Age-Invariant Face Recognition
https://github.com/neverUseThisName/Face-X-Ray
https://github.com/ngonthier/multiresolution_texture
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nguoido/Yolo-alexeyAB
https://github.com/nhanvu39/ArcFace
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/nhatduy19599/insightface-master
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/nicaogr/multiresolution_texture
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nicku-a/Weather_Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nicolalandro/Padam
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nidolow/image-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/nii-yamagishilab/ClassNSeg
Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
https://github.com/nikitakaraevv/pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.