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adversarial-automixup

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albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

albumentations_examples

Augmentations usage examples for albumentations library

alignmixup_cvpr22

Official Implementation of AlignMixup - CVPR 2022

auggan-cross-domain-adaptation-with-gan-based-dataaugmentation

Advanced data augmentation with Generative Adversarial Networks for vehicle detection

augly

A data augmentations library for audio, image, text, and video.

augmax

[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.

augmentation-for-lnl

[CVPR 2021] Code for "Augmentation Strategies for Learning with Noisy Labels".

augmentor

Image augmentation library in Python for machine learning.

augmix

AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

automold--road-augmentation-library

This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.

awesome-data-augmentation

This is a list of awesome methods about data augmentation.

aws-ohl-autoaug

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

cap_augmentation

Cut and paste augmentation for object detection and instance segmentation

cda

Official PyTorch implementation of the “Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation” (ICCV 2021)

classmix

co-mixup

Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)

cooperative_training_and_latent_space_data_augmentation

[MICCAI 2021 Oral] Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

copy-paste-aug

Copy-paste augmentation for segmentation and detection tasks

copy-paste-for-semantic-segmentation

Unofficial implementation of Copy-Paste method：Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

cut-thumbnail

Official Pytorch implementation of Cut-Thumbnail

cutblur

Rethinking Data Augmentation for Image Super-resolution (CVPR 2020)

cvpr21_pass

PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"

da-sac

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021)

da_ner

“Style Transfer as Data Augmentation: A Case Study on Named Entity Recognition” (EMNLP 2022)

dacov2022

dada

The official code for DADA: Differentiable Automatic Data Augmentation (ECCV20)

data_augmentation_zoo_for_object_detection

Includes: Learning data augmentation strategies for object detection | GridMask data augmentation | Augmentation for small object detection in Numpy. Use RetinaNet with ResNet-18 to test these methods on VOC and KITTI.

fast-autoaugment

Official Implementation of 'Fast AutoAugment' in PyTorch.

fda

Fourier Domain Adaptation for Semantic Segmentation