Here are
50 public repositories
matching this topic...
PyTorch implementation of CNNs for CIFAR benchmark
Updated
Feb 20, 2021
Python
Implementation of the mixup training method
Updated
Jun 12, 2018
Python
🛠 Toolbox to extend PyTorch functionalities
Updated
Oct 31, 2021
Python
An implementation of "mixup: Beyond Empirical Risk Minimization"
Updated
Nov 5, 2017
Jupyter Notebook
TextAugment: Text Augmentation Library
Updated
Sep 15, 2021
Python
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)
Updated
Dec 26, 2020
Python
mixup: Beyond Empirical Risk Minimization
Updated
Jan 2, 2018
Python
Data Augmentation For Object Detection using Pytorch and PIL
Updated
Aug 1, 2020
Jupyter Notebook
Oriented Object Detection: Oriented RepPoints + Swin Transformer/ReResNet
Updated
Dec 25, 2021
Python
Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.
Updated
Jul 3, 2020
Jupyter Notebook
Source codes for the paper "Local Additivity Based Data Augmentation for Semi-supervised NER"
Updated
Oct 20, 2020
Python
an implementation of mixup
Updated
Aug 6, 2020
Python
Official adversarial mixup resynthesis repository
Updated
Feb 14, 2020
Python
An implementation of MobileNetV3 with pyTorch
Updated
Jul 24, 2020
Python
Review materials for the TWiML Study Group. Contains annotated versions of the original Jupyter noteboooks (look for names like *_jcat.ipynb ), slide decks from weekly Zoom meetups, etc.
Updated
Jan 25, 2020
Jupyter Notebook
How to do mixup training from image files in Keras
Updated
Jan 13, 2019
Jupyter Notebook
ManifoldMixup with support for Interpolated Adversarial training
Updated
Mar 10, 2020
Jupyter Notebook
Mixup for Supervision, Semi- and Self-Supervision Learning Toolbox and Benchmark
Updated
Apr 8, 2022
Python
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.
Updated
Jun 26, 2021
Python
tensorflow2 implementation of SnapMix as described in SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data
Updated
Feb 4, 2021
Python
Implementation of semi-supervised learning: UDA, MixMatch, Mean-teacher, focusing on NLP, powered by Pytorch
Updated
Jan 6, 2021
Python
Official implementation for ACL2021 Oral Paper: "OoMMix: Out-of-manifold Regularization in Contextual Embedding Space for Text Classification"
Updated
May 24, 2021
Jupyter Notebook
Official Codes and Pretrained Models for RecursiveMix
Updated
Mar 15, 2022
Python
Exploring mixup strategies for text classification
Updated
Dec 16, 2020
Python
📦 Simple Tool Box with Pytorch
Updated
Jan 27, 2021
Python
[TMI'20] Learn to Threshold: ThresholdNet with Confidence-Guided Manifold Mixup for Polyp Segmentation
Updated
Jun 17, 2021
Python
A handy data augmentation toolkit for image classification put in a single efficient TensorFlow op.
Updated
Mar 31, 2022
Python
Tensorflow2/KerasのImageDataGenerator向けのmixupの実装。
Updated
Jun 8, 2020
Jupyter Notebook
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HI, the repo is a nice work, thanks for your sharing.
I want to know if these augmentation methods are effective,
like the RandomErasing/Mixup/RandAugment/Cutout/CutMix?