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/OFRIN/Tensorflow_RetinaFace
https://github.com/OPAYA/Transformer
https://github.com/ORB-HD/deface
CenterFace: Joint Face Detection and Alignment Using Face as Point
https://github.com/OUC-VAS/FacePoison
Hiding Faces in Plain Sight: Defending DeepFakes by Disrupting Face Detection
https://github.com/OlafenwaMoses/Action-Net
https://github.com/OlafenwaMoses/IdenProf
https://github.com/OlafenwaMoses/Traffic-Net
https://github.com/Olayemiy/Image-Classification-With-Resnet
https://github.com/Olksndr/FaceShifter
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/OmarEl-Khashab/FerNeXt-Facial-Expression-Recognition-Using-ConvNeXt-with-Channel-Attention
https://github.com/One-sixth/CVAE-GAN_tensorlayer
CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training
https://github.com/Ontheway361/dul-pytorch
https://github.com/Ontheway361/pfld-pytorch
https://github.com/Oorgien/Scene-Inpainting
https://github.com/OpenTalker/SadTalker
https://github.com/PPPrior/i3d-pytorch
https://github.com/PaParaZz1/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/PacktPublishing/Hands-On-Image-Generation-with-TensorFlow-2.0/tree/master/Chapter07
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/PaddlePaddle/PLSC
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/PaddlePaddle/PaddleSeg
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/Panagiotou/Procedural3DTerrain
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Panagiotou/Random3DTerrain
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Phimos/Paddle-PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/PietroMelzi/GANDiffFace
Synthetic Data for the Mitigation of Demographic Biases in Face Recognition
https://github.com/Podidiving/lgsc-for-fas-pytorch
https://github.com/PolarisAlpha/darknet
https://github.com/PolyArch/fp-diannao
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Popoooo/darknet_test
https://github.com/Porechniy13/FaceReco
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/PowerOfDream/digitx
https://github.com/PrasannaPulakurthi/ProGAN_PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/PrashantRanjan09/Structured-Self-Attentive-Sentence-Embedding
https://github.com/PrashanthaTP/wav2mov
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
https://github.com/Prateek93a/DoodleAI
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.