城西小楼's repositories
segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
AutoAugment
Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow
awesomeCV
记录state-of-art计算机视觉相关论文。
BASNet
Code for CVPR 2019 paper. BASNet: Boundary-Aware Salient Object Detection
catalyst
Reproducible and fast DL & RL
CBAM.PyTorch
Non-official implement of Paper：CBAM: Convolutional Block Attention Module
COVID-Net
COVID-Net Open Source Initiative
CVPR2019-Code
CVPR 2019 Paper with Code
deeplearning-models
A collection of various deep learning architectures, models, and tips
detectron2
Detectron2 is FAIR's next-generation research platform for object detection and segmentation.
faster-rcnn.pytorch
A faster pytorch implementation of faster r-cnn
learnGitBranching
An interactive git visualization to challenge and educate!
libpku
贵校课程资料民间整理
MA-CNN
Multi-Attention-CNN
metric-learning-divide-and-conquer
Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019
nni
An open source AutoML toolkit for neural architecture search and hyper-parameter tuning.
pretrained-models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
pumpkin-book
《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book
pytorch-image-models
PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more
pytorch-loss
label-smooth, amsoftmax, focal-loss, triplet-loss. Maybe useful
PyTorch_Tutorial
《Pytorch模型训练实用教程》中配套代码
siamese-triplet
Siamese and triplet networks with online pair/triplet mining in PyTorch
Skin-Cancer-Classification
Classification of Skin Cancer Images - ResNet
the-craft-of-selfteaching
One has no future if one couldn't teach themself.
torchcv
A PyTorch-Based Framework for Deep Learning in Computer Vision
vimplus
:rocket:An automatic configuration program for vim