Papers with Code 아카이브
3D Face Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 9
- 보존된 평가 기록
- 94
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/setharram/facenet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/sevenHsu/Face_Recognition_IN_Video
https://github.com/seyrankhademi/ResNet_CIFAR10
https://github.com/sgrvinod/a-pytorch-tutorial-to-super-resolution
https://github.com/shahbuland/basic-gans
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/shahidul56/Tiny_Faces_in_Tensorflow_msc
https://github.com/shanxuanchen/FacialExpressionRecognition
Island Loss for Learning Discriminative Features in Facial Expression Recognition
https://github.com/shao-chi/ImageCaption
https://github.com/shariff94/Facial_Keypoint_Detection
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/shashigharti/secure-privateai-scholarship-challenge
https://github.com/shenwei1231/caffe-DeepRegressionForests
https://github.com/sherkhan15/distarctor-Detection_Eyes_Emotions_CI
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/shi510/ffem
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/shijianjian/HRNet_Keras
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/shijianjian/efficientnet-pytorch-3d
https://github.com/shijx12/AR-Tree
https://github.com/shinyingl/CV_Facial_Keypoints
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/shiqiyu/libfacedetection.train
https://github.com/shoaibahmed/CrossLayerPooling
https://github.com/shoji9x9/CIFAR-10-By-small-ResNet
https://github.com/shoji9x9/Fashion-MNIST-By-ResNet
https://github.com/shoutOutYangJie/Few-Shot-Adversarial-Learning-for-face-swap
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
https://github.com/shridharrhegde/vgg-age
Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model
https://github.com/shtnkgm/VisionFrameworkSample
https://github.com/shuShelby/main
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/shuliyao/GANimation_TL
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/shuuchen/HRNet
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/shyhyawJou/ArcFace-Pytorch
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/sibozhang/Text2Video
https://github.com/sicxu/Deep3DFaceRecon_pytorch
https://github.com/siddharthbhonge/Neural_Style_transfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/sidify/resnet_focal_loss
https://github.com/sidward14/gan-lab
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/sijinkim/pggan-clone
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/simo-bat/Crack_detection
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.