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/mohaEs/Train-Predict-Landmarks-by-flat-net
Automatic vocal tract landmark localization from midsagittal MRI data
https://github.com/mohammadimathstar/grlgq
https://github.com/mohanliu/HRnet-semantic-segmentation-exp
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/mohitwildbeast/Facial-Recognition-Using-FaceNet-Siamese-One-Shot-Learning
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/moron96/FaceRecogLDAP
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mosmos/face_key_point_detection
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/mowshon/lipsync
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
https://github.com/mrpintime/Face-Liveness-TensorFlow
Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
https://github.com/mrv8x/DeepFaceLab
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/mrw-soumik/Tiny-Faces-in-Tensorflow
https://github.com/msaadsaeed/sbnet
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/mseg-dataset/mseg-semantic
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/mshehrozsajjad/Age-Classification
Rank consistent ordinal regression for neural networks with application to age estimation
https://github.com/mszpc/facenet_ascend
FaceNet: A Unified Embedding for Face Recognition and Clustering
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/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/negarhdr/skeleton-based-action-recognition
https://github.com/nelson-mig-l/boofcv-dithering
https://github.com/neshitov/UNet
https://github.com/neuralet/facemask
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.