Utilizing machine learning models to generate refined depth maps with segmentation mask guidance
US12367585B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 12, 2022 |
| Grant date | Jul 22, 2025 |
| Priority date | — |
| Expiry date | Dec 1, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing machine learning models to generate refined depth maps of digital images utilizing digital segmentation masks. In particular, in one or more embodiments, the disclosed systems generate a depth map for a digital image utilizing a depth estimation machine learning model, determine a digital segmentation mask for the digital image, and generate a refined depth map from the depth map and the digital segmentation mask utilizing a depth refinement machine learning model. In some embodiments, the disclosed systems generate first and second intermediate depth maps using the digital segmentation mask and an inverse digital segmentation mask and merger the first and second intermediate depth maps to generate the refined depth map.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.