Visual localization in images using weakly supervised neural network
US11216927B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 16, 2018 |
| Grant date | Jan 4, 2022 |
| Priority date | — |
| Expiry date | Jan 6, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20216
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method for visual anomaly localization in a test image includes generating, in plurality of scaled iterations, attention maps for a test image using a trained classifier network, using image-level. A current attention map is generated using an inversion of the classifier network on a condition that a forward pass of the test image in the classifier network detects a first class. One or more attention regions of the current attention map may be extracted and resized as a sub-image. For each scaled iteration, extraction of one or more regions of a current attention map is performed on a condition that the current attention map is significantly different than the preceding attention map. Visual localization of a region for the class in the test image is based on one or more of the attention maps.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.