There are 40 repositories under self-supervised-learning topic.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
OpenMMLab Pre-training Toolbox and Benchmark
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
A python library for self-supervised learning on images.
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
A Semantic Controllable Self-Supervised Learning Framework to learn general human representations from massive unlabeled human images, which can benefit downstream human-centric tasks to the maximum extent
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"
The official repo for [NeurIPS'22] "ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation" and [TPAMI'23] "ViTPose++: Vision Transformer for Generic Body Pose Estimation"
A comprehensive list of awesome contrastive self-supervised learning papers.
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
Unsupervised Feature Learning via Non-parametric Instance Discrimination
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
[MICCAI 2019] [MEDIA 2020] Models Genesis
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).
DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
All-in-one Toolbox for Computer Vision Research.
ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"
This is an official implementation for "Self-Supervised Learning with Swin Transformers".
[CVPR 2021] Self-supervised depth estimation from short sequences