Utilizing generative models for resynthesis of transition frames in clipped digital videos
US12192593B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 3, 2023 |
| Grant date | Jan 7, 2025 |
| Priority date | — |
| Expiry date | Aug 2, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N21/23424
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine learning to generate a sequence of transition frames for a gap in a clipped digital video. For example, the disclosed system receives a clipped digital video that includes a pre-cut frame prior to a gap in the clipped digital video and a post-cut frame following the gap in the clipped digital video. Moreover, the disclosed system utilizes a natural motion sequence model to generates a sequence of transition keypoint maps between the pre-cut frame and the post-cut frame. Furthermore, using a generative neural network, the disclosed system generates a sequence of transition frames for the gap in the clipped digital video from the sequence of transition keypoint maps.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.