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AutoStyle: Automatic Style Transfer from Image Collections to Users' Images
Author(s) -
Liu Yiming,
Cohen Michael,
Uyttendaele Matt,
Rusinkiewicz Szymon
Publication year - 2014
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12409
Subject(s) - computer science , vignetting , filter (signal processing) , set (abstract data type) , artificial intelligence , style (visual arts) , computer vision , information retrieval , range (aeronautics) , image (mathematics) , computer graphics (images) , art , programming language , materials science , literature , petroleum engineering , engineering , composite material , lens (geology)
Stylizing photos, to give them an antique or artistic look, has become popular in recent years. The available stylization filters, however, are usually created manually by artists, resulting in a narrow set of choices. Moreover, it can be difficult for the user to select a desired filter, since the filters’ names often do not convey their functions. We investigate an approach to photo filtering in which the user provides one or more keywords, and the desired style is defined by the set of images returned by searching the web for those keywords. Our method clusters the returned images, allows the user to select a cluster, then stylizes the user's photos by transferring vignetting, color, and local contrast from that cluster. This approach vastly expands the range of available styles, and gives each filter a meaningful name by default. We demonstrate that our method is able to robustly transfer a wide range of styles from image collections to users’ photos.