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Data Augmentation

358 papers with code · Methodology

( Image credit: Albumentations )

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AutoAugment: Learning Augmentation Policies from Data

24 May 2018tensorflow/models

In our implementation, we have designed a search space where a policy consists of many sub-policies, one of which is randomly chosen for each image in each mini-batch.

FINE-GRAINED IMAGE CLASSIFICATION IMAGE AUGMENTATION

YOLOv4: Optimal Speed and Accuracy of Object Detection

23 Apr 2020pjreddie/darknet

There are a huge number of features which are said to improve Convolutional Neural Network (CNN) accuracy.

DATA AUGMENTATION REAL-TIME OBJECT DETECTION

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

18 Apr 2019mozilla/DeepSpeech

On LibriSpeech, we achieve 6. 8% WER on test-other without the use of a language model, and 5. 8% WER with shallow fusion with a language model.

DATA AUGMENTATION END-TO-END SPEECH RECOGNITION LANGUAGE MODELLING SPEECH RECOGNITION

Sampling Generative Networks

14 Sep 2016soumith/ganhacks

We introduce several techniques for sampling and visualizing the latent spaces of generative models.

DATA AUGMENTATION

Albumentations: fast and flexible image augmentations

18 Sep 2018albu/albumentations

We provide examples of image augmentations for different computer vision tasks and show that Albumentations is faster than other commonly used image augmentation tools on the most of commonly used image transformations.

IMAGE AUGMENTATION

RandAugment: Practical automated data augmentation with a reduced search space

30 Sep 2019rwightman/pytorch-image-models

Additionally, due to the separate search phase, these approaches are unable to adjust the regularization strength based on model or dataset size.

 SOTA for Image Classification on CIFAR-10 (Top 1 Accuracy metric )

DATA AUGMENTATION IMAGE CLASSIFICATION OBJECT DETECTION

Random Erasing Data Augmentation

16 Aug 2017rwightman/pytorch-image-models

In this paper, we introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN).

IMAGE AUGMENTATION IMAGE CLASSIFICATION OBJECT DETECTION PERSON RE-IDENTIFICATION

Pythia v0.1: the Winning Entry to the VQA Challenge 2018

26 Jul 2018facebookresearch/mmf

We demonstrate that by making subtle but important changes to the model architecture and the learning rate schedule, fine-tuning image features, and adding data augmentation, we can significantly improve the performance of the up-down model on VQA v2. 0 dataset -- from 65. 67% to 70. 22%.

DATA AUGMENTATION VISUAL QUESTION ANSWERING

Self-training with Noisy Student improves ImageNet classification

CVPR 2020 tensorflow/tpu

During the learning of the student, we inject noise such as dropout, stochastic depth, and data augmentation via RandAugment to the student so that the student generalizes better than the teacher.

#2 best model for Image Classification on ImageNet (using extra training data)

DATA AUGMENTATION IMAGE CLASSIFICATION

Learning Data Augmentation Strategies for Object Detection

26 Jun 2019tensorflow/tpu

Importantly, the best policy found on COCO may be transferred unchanged to other detection datasets and models to improve predictive accuracy.

IMAGE AUGMENTATION IMAGE CLASSIFICATION OBJECT DETECTION