Training and using an ensemble of complimentary convolutional neural networks for cross-domain retrieval of fashion item images
US11443468B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 4, 2020 |
| Grant date | Sep 13, 2022 |
| Priority date | — |
| Expiry date | Jun 16, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2210/22
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system generate an ensemble image representation for cross-domain retrieval of a fashion item image from a database by using a three-stream Siamese triplet loss trained convolutional neural network to generate a first retrieval descriptor corresponding to an inputted query image; using an average precision loss trained convolutional neural network to generate a second retrieval descriptor corresponding to the inputted query image; concatenating both the first retrieval descriptor and the second retrieval descriptor; and I2-normalizing the concatenated result to generate the ensemble image representation. During a first stage of the method and system, database items are cropped using a trained fine-grained fashion item detector.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.