XiaochangHu's repositories
Awesome-Incremental-Learning
Awesome Incremental Learning
RODNet
RODNet: Radar object detection network
self-label
Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)
LIO-SAM
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
awesome-normalization-techniques
Papers for normalization techniques, released codes collections.
Continual-Learning-Benchmark
Evaluate three types of task shifting with popular continual learning algorithms.
PseudoLabeling
Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"
Deep-SAD-PyTorch
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
realistic-ssl-evaluation-pytorch
Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"
FewShotPapers
This repository contains few-shot learning (FSL) papers mentioned in our FSL survey.
gluon-cv
Gluon CV Toolkit
imbalanced-dataset-sampler
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
FMix
Official implementation of 'Understanding and Enhancing Mixed Sample Data Augmentation'
Tricks-of-Semi-supervisedDeepLeanring-Pytorch
PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch
awesome-semi-supervised-learning
:scroll: A curated list of awesome semi-supervised learning methods & papers.
torch-toolbox
[Active development]ToolBox to make using Pytorch much easier.
Dassl.pytorch
A PyTorch toolbox for domain adaptation and semi-supervised learning.
SSL-NAG
Semi-Supervised Learning with nonlinear representation and adaptive graph
semisup-learn
Semi-supervised learning frameworks for python, which allow fitting scikit-learn classifiers to partially labeled data
Bag_of_Tricks_for_Image_Classification_with_Convolutional_Neural_Networks
experiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc
GridCell
TensorFlow code for paper: Learning Grid-like Units with Vector Representation of Self-Position and Matrix Representation of Self-Motion
mantis
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
ssl_graph
Semi supervised learning on graphs
stanford_self_driving_car_code
Stanford Code From Cars That Entered DARPA Grand Challenges