AVA: A Large-Scale Database for Aesthetic Visual Analysis
Naila Murray and Luca Marchesotti and Florent Perronnin



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AVA_dataset (92 files)
images/images.7z.035524.29MB
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images/images.7z.06499.06MB
README.txt3.87kB
aesthetics_image_lists/fooddrink_train.jpgl19.99kB
aesthetics_image_lists/floral_test.jpgl19.78kB
aesthetics_image_lists/floral_train.jpgl19.77kB
aesthetics_image_lists/stilllife_test.jpgl19.30kB
aesthetics_image_lists/architecture_train.jpgl19.61kB
aesthetics_image_lists/architecture_test.jpgl19.61kB
aesthetics_image_lists/generic_ls_train.jpgl157.38kB
aesthetics_image_lists/portrait_test.jpgl19.70kB
aesthetics_image_lists/landscape_train.jpgl19.72kB
aesthetics_image_lists/generic_test.jpgl157.30kB
aesthetics_image_lists/animal_test.jpgl19.67kB
aesthetics_image_lists/generic_ss_train.jpgl19.70kB
aesthetics_image_lists/cityscape_test.jpgl19.52kB
aesthetics_image_lists/portrait_train.jpgl19.74kB
aesthetics_image_lists/stilllife_train.jpgl19.31kB
aesthetics_image_lists/animal_train.jpgl19.68kB
aesthetics_image_lists/cityscape_train.jpgl19.56kB
aesthetics_image_lists/landscape_test.jpgl19.73kB
aesthetics_image_lists/fooddrink_test.jpgl19.99kB
style_image_lists/test.multilab81.46kB
style_image_lists/styles.txt0.22kB
style_image_lists/test.jpgl22.01kB
style_image_lists/train.jpgl88.32kB
style_image_lists/train.lab38.04kB
tags.txt0.95kB
challenges.txt26.98kB
AVA.txt12.49MB
Type: Dataset
Tags: semantic, quality, AVA, DPChallenge, images, aesthetics

Bibtex:
@article{,
title= {AVA: A Large-Scale Database for Aesthetic Visual Analysis},
keywords= {images, aesthetics, semantic, quality, AVA, DPChallenge},
journal= {},
author= {Naila Murray and Luca Marchesotti and Florent Perronnin},
year= {},
url= {},
license= {},
abstract= {Aesthetic Visual Analysis (AVA) contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style for high-level image quality categorization.},
superseded= {},
terms= {}
}