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Data Augmentation

186 papers with code · Methodology

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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.

DATA AUGMENTATION FINE-GRAINED IMAGE CLASSIFICATION

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.

DATA AUGMENTATION

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

26 Jul 2018facebookresearch/pythia

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

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.

DATA AUGMENTATION IMAGE CLASSIFICATION OBJECT DETECTION

DSFD: Dual Shot Face Detector

CVPR 2019 TencentYoutuResearch/FaceDetection-DSFD

In this paper, we propose a novel face detection network with three novel contributions that address three key aspects of face detection, including better feature learning, progressive loss design and anchor assign based data augmentation, respectively.

DATA AUGMENTATION FACE 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).

DATA AUGMENTATION IMAGE CLASSIFICATION OBJECT DETECTION PERSON RE-IDENTIFICATION

Camera Style Adaptation for Person Re-identification

CVPR 2018 layumi/Person_reID_baseline_pytorch

With LSR, we demonstrate consistent improvement in all systems regardless of the extent of over-fitting.

DATA AUGMENTATION PERSON RE-IDENTIFICATION

NiftyNet: a deep-learning platform for medical imaging

11 Sep 2017NifTK/NiftyNet

NiftyNet provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications.

DATA AUGMENTATION IMAGE GENERATION MEDICAL IMAGE GENERATION REPRESENTATION LEARNING