solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
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Updated
Dec 23, 2024 - Python
solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
Self-Supervised Learning in PyTorch
Collections of self-supervised methods, based on cvpods.
An easy-to-use implementation of Barlow Twins for Pytorch.
Official PyTorch Implementation of Guarding Barlow Twins Against Overfitting with Mixed Samples
Codebase for Imperial MSc AI Individual Project - Self-Supervised Learning for Audio Inference
Official implementation of "Augmentation-aware Self-supervised Learning with Conditioned Projector"
Exploring Self-Supervised Learning for Low-Resource Medical Image Analysis, ICIP 2023
Barlow Twins for Scanpath prediction on paintings
Context Aware Predictive Coding (CAPC)
This project utilized Self-Supervised learning methods (SimCLR & SimSiam) to recognize vehicle-type (or any object) based on a custom dataset
This repository contains the code for continual barlow twins with embedding regularizer as a continual learning technique.
Contrastive learning implementations using pyssl
In this project, we propose to study Vision Transformers trained using the Barlow Twins self-supervised method, and compare the results with DINO. We demonstrate the effectiveness of the Barlow Twins method by showing that networks pretrained on the small PASCAL VOC 2012 dataset are able to generalize well. Authors: Apavou Clément & Zucker Arthur
Implementation of Barlow Twins: Self-Supervised Learning via Redundancy Reduction with `timm` integration
Can Self-Supervised Representation Learning Methods Withstand Distribution Shifts and Corruptions? (ICCV Workshops 2023)
Copy of assignments submitted to the course-work of DL_425
Implementation of Barlow Twins in Pytorch
Self supervised Learning On resnet 15 using Custom Generative adverisal Network to generate Images of the labelled and Unlabeled images dataset
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