Invention Application
- Patent Title: GUIDED HALLUCINATION FOR MISSING IMAGE CONTENT USING A NEURAL NETWORK
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Application No.: US16353195Application Date: 2019-03-14
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Publication No.: US20190355103A1Publication Date: 2019-11-21
- Inventor: Seung-Hwan Baek , Kihwan Kim , Jinwei Gu , Orazio Gallo , Alejandro Jose Troccoli , Ming-Yu Liu , Jan Kautz
- Applicant: NVIDIA Corporation
- Main IPC: G06T5/00
- IPC: G06T5/00 ; G06K9/72 ; G06T5/50 ; G06T3/40 ; G06K9/62

Abstract:
Missing image content is generated using a neural network. In an embodiment, a high resolution image and associated high resolution semantic label map are generated from a low resolution image and associated low resolution semantic label map. The input image/map pair (low resolution image and associated low resolution semantic label map) lacks detail and is therefore missing content. Rather than simply enhancing the input image/map pair, data missing in the input image/map pair is improvised or hallucinated by a neural network, creating plausible content while maintaining spatio-temporal consistency. Missing content is hallucinated to generate a detailed zoomed in portion of an image. Missing content is hallucinated to generate different variations of an image, such as different seasons or weather conditions for a driving video.
Public/Granted literature
- US10922793B2 Guided hallucination for missing image content using a neural network Public/Granted day:2021-02-16
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