Image generation model based on log-likelihood
US11995151B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 25, 2021 |
| Grant date | May 28, 2024 |
| Priority date | — |
| Expiry date | Sep 27, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/80
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method of training an image generation model. The image generation model comprises an argmax transformation configured to compute a discrete index feature indicating an index of a feature of the continuous feature vector with an extreme value. The image generation model is trained using a log-likelihood optimization. This involves obtaining a value of the index feature for the training image, sampling values of the continuous feature vector given the value of the index feature according to a stochastic inverse transformation of the argmax transformation, and determining a likelihood contribution of the argmax transformation for the log-likelihood based on a probability that the stochastic inverse transformation generates the values of the continuous feature vector given the value of the index feature.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.