Self-Supervised Learning

Last update: Dec 14, 2021

Overview

Self-Supervised Learning

Features

self_supervised offers features like

modular framework
support for multi-gpu training using PyTorch Lightning
easy to use and written in a PyTorch like style
supports custom backbone models for self-supervised pre-training

Supported Models

Supported Loss Function

Benchmarks

Currently implemented models and their accuracy on cifar10 and imagenette.

ImageNette

Model	Epochs	Batch Size	Test Accuracy
MoCo	800	256	0.827
SimCLR	800	256	0.847
SimSiam	800	256	0.827
BarlowTwins	800	256	0.801
BYOL	800	256	0.851

Cifar10

Model	Epochs	Batch Size	Test Accuracy
MoCo	200	128	0.83
SimCLR	200	128	0.78
SimSiam	200	128	0.73
BarlowTwins	200	128	0.84
BYOL	200	128	0.85
MoCo	200	512	0.85
SimCLR	200	512	0.83
SimSiam	200	512	0.81
BarlowTwins	200	512	0.78
BYOL	200	512	0.84
MoCo	800	128	0.89
SimCLR	800	128	0.87
SimSiam	800	128	0.80
MoCo	800	512	0.90
SimCLR	800	512	0.89
SimSiam	800	512	0.91

Tutorials

Want to jump to the tutorials and see lightly in action?

Self-Supervised Learning

Related tags

Overview

Self-Supervised Learning

Features

Supported Models

Supported Loss Function

Benchmarks

ImageNette

Cifar10

Tutorials

Further Reading

Owner

Robin

Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?

RuDOLPH: One Hyper-Modal Transformer can be creative as DALL-E and smart as CLIP

PyTorch implementation of spectral graph ConvNets, NIPS’16

small collection of functions for neural networks

DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation

Reinforcement learning algorithms in RLlib

Code release for ConvNeXt model

Merlion: A Machine Learning Framework for Time Series Intelligence

Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals

Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

SOFT: Softmax-free Transformer with Linear Complexity, NeurIPS 2021 Spotlight

[ICCV 2021 Oral] Deep Evidential Action Recognition

Pytorch implementation of "Geometrically Adaptive Dictionary Attack on Face Recognition" (WACV 2022)

Semi-supervised Transfer Learning for Image Rain Removal. In CVPR 2019.

Code repo for EMNLP21 paper "Zero-Shot Information Extraction as a Unified Text-to-Triple Translation"

Visual dialog agents with pre-trained vision-and-language encoders.

Our solution for SSN Invente 2021's Hackathon

A CV toolkit for my papers.

Official implementation of ETH-XGaze dataset baseline

Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation (CoRL 2021)