An unofficial implementation of Google Brain's research in 2018
-
Updated
Jan 17, 2020 - Python
An unofficial implementation of Google Brain's research in 2018
RandAugment process for point cloud data to handle with 3D classification task
PyTorch implementation of AutoAugment.
Code for "OnlineAugment: Online Data Augmentation with Less Domain Knowledge" (ECCV 2020)
Unofficial PyTorch Reimplementation of UniformAugment.
Stanford CS 230 Group Project
Optimize RandAugment with differentiable operations
📦Simple Tool Box with Pytorch
Unofficial Pytorch Implementation Of AdversarialAutoAugment(ICLR2020)
FastClassification is a tensorflow toolbox for class classification. It provides a training module with various backbones and training tricks towards state-of-the-art class classification.
Unofficial Pytorch implementation of the paper 'Learning Data Augmentation Strategies for Object Detection'
Comparing different learning paradigms on the STL 10 dataset and carrying further analysis in each method
Collection of deep learning modules
This repository contains the code and the report for the coursework of INFR11031 Advanced Vision, a postgraduate course offered at The University of Edinburgh. The task was to train on limited and improve the accuracy of the ResNet-50 classifier on a small subset of the ImageNet dataset containing 50K training images and 50K test images. Achieve…
Official PyTorch code for CVPR 2021 paper "AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation"
Unofficial PyTorch Reimplementation of RandAugment.
Predefined pipelines for image augmentation
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
🛠 Toolbox to extend PyTorch functionalities
PyTorch implementation of Fast AutoAugment for Time Series
Add a description, image, and links to the autoaugment topic page so that developers can more easily learn about it.
To associate your repository with the autoaugment topic, visit your repo's landing page and select "manage topics."