Guided hallucination for missing image content using a neural network
US10922793B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 14, 2019 |
| Grant date | Feb 16, 2021 |
| Priority date | — |
| Expiry date | Jun 5, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.