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PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
PyTorch implementation of Contrastive Learning methods
上海交通大学 LaTeX 论文模板 | Shanghai Jiao Tong University LaTeX Thesis Template
An unofficial Pytorch implementation of "Improved Baselines with M 8000 omentum Contrastive Learning" (MoCoV2) - X. Chen, et al.
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
Unofficial implementation with pytorch DistributedDataParallel for "MoCo: Momentum Contrast for Unsupervised Visual Representation Learning"
PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
This is a warehouse for DeiT-pytorch-model, can be used to train your image dataset
Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Ready to train Pytorch implementation of the CVPR'19 paper "Self-Supervised GANs via Auxiliary Rotation Loss"
My pytorch implementation of 'SelfGAN--Not A GAN But Punch Itself'.
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
This project utilized Self-Supervised learning methods (SimCLR & SimSiam) to recognize vehicle-type (or any object) based on a custom dataset
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
Pytorch Implementation of One Shot Learning for Face Recognition
I have implemented a Face Recognition & Face Verification model by One Shot Learning using the Triplet Loss function
Pytorch implementation of one shot learning for facial embedding
koch et al, Siamese Networks for one-shot learning, (mostly) reimplimented in keras
Facenet implementation by Keras2
MTCNN face detection implementation for TensorFlow, as a PIP package.
Face recognition using triplet loss, implementing FaceNet with pytorch.人脸识别项目，提供一个小型数据集用作验证，使用三元组损失函数(Triplet loss)提升准确率和泛化能力，对FaceNet进行了一种实现。
Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models
Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch Version (https://github.com/AlfredXiangWu/LightCNN)