Scene completion using millions of photographs
Scene completion using millions of photographs
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DOI：
10.1145/1276377.1276382
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发表时间：
2007-07-01
影响因子：
6.2
通讯作者：
Efros, Alexei A.
中科院分区：
文献类型：
--
作者：
Hays, James;Efros, Alexei A.
你能用一百万张图片做什么？在本文中，我们提出了一个新的图像完成算法，由一个巨大的数据库从网络上收集的照片。该算法通过在数据库中找到相似的图像区域来修补图像中的漏洞，这些区域不仅是无缝的，而且是语义有效的。我们的主要见解是，虽然图像的空间实际上是无限的，但语义可微场景的空间实际上并没有那么大。对于许多图像完成任务，我们能够找到包含图像片段的类似场景，这些场景将令人信服地完成图像。我们的算法完全是数据驱动的，不需要用户的注释或标签。与现有的图像完成方法不同，我们的算法可以为每个输入图像生成一组不同的结果，我们允许用户在其中进行选择。我们证明了我们的算法优于现有的图像完成方法。
What can you do with a million images? In this paper we 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. Our chief insight is that while the space of images is effectively infinite, the space of semantically differentiable scenes is actually not that large. For many image completion tasks we are able to find similar scenes which contain image fragments that will convincingly complete the image. Our algorithm is entirely data-driven, requiring no annotations or labelling by the user. Unlike existing image completion methods, our algorithm can generate a diverse set of results for each input image and we allow users to select among them. We demonstrate the superiority of our algorithm over existing image completion approaches.