What can you do with a million images? In this paper James Hays and Alexei Efros, present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. For many image completion tasks we are able to find similar scenes which contain image fragments that will convincingly complete the image. Their algorithm is entirely data-driven, requiring no annotations or labeling by the user. Unlike existing image completion methods, their algorithm can generate a diverse set of image completions and allowing users to select among them.
Scene Completion Using Millions of Photographs
About the Author: Carlos Pinho
A father, a husband and a geek... Carlos was the founder of projects like The Tech Labs and Flash Enabled Blog. He is the founder of TekTuts He is passionate about technologies. Their main skills are in analytics, transport & logistics, business administration. He also writes about programming resources, trends, strategy and web development.