Papers with Code 아카이브
Face Reconstruction
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Face reconstruction is the task of recovering the facial geometry of a face from an image.
<span style="color:grey; opacity: 0.6">( Image credit: Microsoft Deep3DFaceReconstruction )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/HarmanDotpy/Normalizations-in-Deep-Learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Harry-Muzart/harry-muzart.github.io
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Harut0726/my-pointnet-tensorflow
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/HavenFeng/photometric_optimization
https://github.com/Hayashi-Yudai/ML_models
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/Hazqeel09/ellzaf_ml
S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens
https://github.com/HearyShen/HAN-SelfAttentive
https://github.com/Heonozis/FaceShifter-pytorch
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/HiJiGOO/self-attentive
https://github.com/Hikaylee/SynergyNet
Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
https://github.com/HongSic/DarknetAI
https://github.com/HongguLiu/MesoNet.Pytorch
https://github.com/HongwenZhang/JVCR-3Dlandmark
https://github.com/Human3DAIGC/AccurateFacialLandmarkDetection
Cascaded Dual Vision Transformer for Accurate Facial Landmark Detection
https://github.com/HyeongJu916/Boaz-SR-ESRGAN-PyTorch
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/IBM/NeuronAlignment
https://github.com/IIGROUP/Multi-Modal-CelebA-HQ-Dataset
TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
https://github.com/IIGROUP/TediGAN
TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
https://github.com/IMvision12/keras-vision-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/IPLI/IPLI_Server
https://github.com/IQTLabs/Pytorch_Retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/IanSullivan/DeepFakeTorch
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
https://github.com/IcedDoggie/Micro-Expression-with-Deep-Learning
Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition
https://github.com/IcewineChen/mxnet-batch_hard_triplet_loss
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/Ierezell/PapierFewShot
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
https://github.com/IlyaOvodov/AngelinaReader
https://github.com/InterDigitalInc/Latent-Transformer
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/Ipsedo/MusicGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/IsharaSandun/Face-Recognition-using-python
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/IssacCyj/Adversarial-Occlussion-aware-Face-Detection
https://github.com/J-woooo/Mask_Remover
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/JContro/pytorch_projects
https://github.com/JHLee0513/Salt_detection_challenge
https://github.com/JONGSKY/paper
https://github.com/Jagannathrk2020/Face-detection-and-counting-
FaceNet: A Unified Embedding for Face Recognition and Clustering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.