PT Unknown
AU Naila Murray
   Luca Marchesotti
   Florent Perronnin
TI AVA: A Large-Scale Database for Aesthetic Visual Analysis
BT 25th IEEE Conference on Computer Vision and Pattern Recognition
PY 2012
BP 2408
EP 2415
DI 10.1109/CVPR.2012.6247954
AB With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It 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. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks
ER