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1.发明申请公开(公告)号：US20160335795A1
公开(公告)日：2016-11-17
申请号：US15154417
申请日：2016-05-13
Applicant: Google Inc.
Inventor： John Flynn , Keith Snavely , Ivan Neulander , James Philbin
IPC: G06T15/20
CPC classification number: G06T15/20 , G06K9/00664 , G06K9/4628 , G06K9/4652 , G06K9/6272 , G06N99/005 , G06T15/205
Abstract: A system and method of deep learning using deep networks to predict new views from existing images may generate and improve models and representations from large-scale data. This system and method of deep learning may employ a deep architecture performing new view synthesis directly from pixels, trained from large numbers of posed image sets. A system employing this type of deep network may produce pixels of an unseen view based on pixels of neighboring views, lending itself to applications in graphics generation.
Abstract translation: 使用深层网络深入学习从现有图像预测新视图的系统和方法可能会生成并改进大型数据的模型和表示。 这种深度学习的系统和方法可以采用深入的架构，直接从像素中执行新的视图合成，从大量呈现的图像集训练。 采用这种类型的深度网络的系统可以基于相邻视图的像素产生不可见视图的像素，从而将其自身应用于图形生成中。
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公开(公告)号：US09916679B2
公开(公告)日：2018-03-13
申请号：US15154417
申请日：2016-05-13
Applicant: Google Inc.
Inventor： John Flynn , Keith Snavely , Ivan Neulander , James Philbin
CPC classification number: G06T15/20 , G06K9/00664 , G06K9/4628 , G06K9/4652 , G06K9/6272 , G06N99/005 , G06T15/205
Abstract: A system and method of deep learning using deep networks to predict new views from existing images may generate and improve models and representations from large-scale data. This system and method of deep learning may employ a deep architecture performing new view synthesis directly from pixels, trained from large numbers of posed image sets. A system employing this type of deep network may produce pixels of an unseen view based on pixels of neighboring views, lending itself to applications in graphics generation.
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