- Patent Title: Deepstereo: learning to predict new views from real world imagery
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Application No.: US15154417Application Date: 2016-05-13
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Publication No.: US09916679B2Publication Date: 2018-03-13
- Inventor: John Flynn , Keith Snavely , Ivan Neulander , James Philbin
- Applicant: Google Inc.
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Brake Hughes Bellermann LLP
- Main IPC: G06T15/20
- IPC: G06T15/20 ; G06K9/00 ; G06K9/62 ; G06K9/46

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.
Public/Granted literature
- US20160335795A1 DEEPSTEREO: LEARNING TO PREDICT NEW VIEWS FROM REAL WORLD IMAGERY Public/Granted day:2016-11-17
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