| deepinsight/insightface |
19,487 |
|
1 |
10 |
over 2 years ago |
28 |
December 17, 2022 |
1,016 |
mit |
Python |
| State-of-the-art 2D and 3D Face Analysis Project |
| timesler/facenet-pytorch |
3,809 |
|
3 |
16 |
over 2 years ago |
32 |
March 10, 2021 |
62 |
mit |
Python |
| Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models |
| ZhaoJ9014/face.evoLVe |
3,074 |
|
0 |
0 |
over 3 years ago |
0 |
|
84 |
mit |
Python |
| 🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥 |
| axinc-ai/ailia-models |
1,708 |
|
0 |
0 |
about 2 years ago |
0 |
|
297 |
|
Python |
| The collection of pre-trained, state-of-the-art AI models for ailia SDK |
| JDAI-CV/FaceX-Zoo |
1,479 |
|
0 |
0 |
over 3 years ago |
0 |
|
103 |
other |
Python |
| A PyTorch Toolbox for Face Recognition |
| kuaikuaikim/DFace |
901 |
|
0 |
0 |
over 7 years ago |
0 |
|
27 |
apache-2.0 |
Python |
| Deep learning face detection and recognition, implemented by pytorch. (pytorch实现的人脸检测和人脸识别) |
| curiousily/Getting-Things-Done-with-Pytorch |
873 |
|
0 |
0 |
almost 5 years ago |
0 |
|
13 |
apache-2.0 |
Jupyter Notebook |
| Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT. |
| wujiyang/Face_Pytorch |
653 |
|
0 |
0 |
over 4 years ago |
0 |
|
52 |
apache-2.0 |
Python |
| face recognition algorithms in pytorch framework, including arcface, cosface, sphereface and so on |
| AlfredXiangWu/LightCNN |
641 |
|
0 |
0 |
about 4 years ago |
0 |
|
0 |
mit |
Python |
| A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018 |
| harveyslash/Facial-Similarity-with-Siamese-Networks-in-Pytorch |
620 |
|
0 |
0 |
almost 6 years ago |
0 |
|
8 |
mit |
Jupyter Notebook |
| Implementing Siamese networks with a contrastive loss for similarity learning |
