Data Augmentation

855 papers with code • 0 benchmarks • 51 datasets

( Image credit: Albumentations )

Greatest papers with code

AutoAugment: Learning Augmentation Policies from Data

tensorflow/models 24 May 2018

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

pjreddie/darknet 23 Apr 2020

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

Data Augmentation Real-Time Object Detection

What Are Bayesian Neural Network Posteriors Really Like?

google-research/google-research 29 Apr 2021

The posterior over Bayesian neural network (BNN) parameters is extremely high-dimensional and non-convex.

Data Augmentation Variational Inference

Learn your ABCs: Approximate Bijective Correspondence for isolating factors of variation

google-research/google-research 4 Mar 2021

We propose a novel algorithm that relies on a weak form of supervision where the data is partitioned into sets according to certain inactive factors of variation.

Data Augmentation Pose Transfer

Large Margin Deep Networks for Classification

google-research/google-research NeurIPS 2018

We present a formulation of deep learning that aims at producing a large margin classifier.

Data Augmentation General Classification

Supervised Contrastive Learning

google-research/google-research NeurIPS 2020

Contrastive learning applied to self-supervised representation learning has seen a resurgence in recent years, leading to state of the art performance in the unsupervised training of deep image models.

Contrastive Learning Data Augmentation +3

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

mozilla/DeepSpeech 18 Apr 2019

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 +2

A Framework For Contrastive Self-Supervised Learning And Designing A New Approach

PyTorchLightning/pytorch-lightning 31 Aug 2020

Contrastive self-supervised learning (CSL) is an approach to learn useful representations by solving a pretext task that selects and compares anchor, negative and positive (APN) features from an unlabeled dataset.

Data Augmentation Image Classification +1

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

rwightman/pytorch-image-models 18 Jun 2021

Vision Transformers (ViT) have been shown to attain highly competitive performance for a wide range of vision applications, such as image classification, object detection and semantic image segmentation.

Data Augmentation Image Classification +2

ResMLP: Feedforward networks for image classification with data-efficient training

rwightman/pytorch-image-models 7 May 2021

We present ResMLP, an architecture built entirely upon multi-layer perceptrons for image classification.

Ranked #5 on Image Classification on ImageNet V2 (using extra training data)

Data Augmentation Fine-Grained Image Classification +3