Video inpainting with deep internal learning
US11055828B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 9, 2019 |
| Grant date | Jul 6, 2021 |
| Priority date | — |
| Expiry date | Oct 14, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques of inpainting video content include training a neural network to perform an inpainting operation on a video using only content from that video. For example, upon receiving video content including a sequence of initial frames, a computer generates a sequence of inputs corresponding to at least some of the sequence of initial frames and each input including, for example, a uniform noise map. The computer then generates a convolutional neural network (CNN) using the sequence of input as the initial layer. The parameters of the CNN are adjusted according to a cost function, which has components including a flow generation loss component and a consistency loss component. The CNN then outputs, on a final layer, estimated image values in a sequence of final frames.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.