Invention Grant
- Patent Title: Method for learning cross-domain relations based on generative adversarial networks
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Application No.: US16295885Application Date: 2019-03-07
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Publication No.: US10713294B2Publication Date: 2020-07-14
- Inventor: Taek Soo Kim , Moon Su Cha , Ji Won Kim
- Applicant: SK TELECOM CO., LTD.
- Applicant Address: KR Seoul
- Assignee: SK TELECOM CO., LTD.
- Current Assignee: SK TELECOM CO., LTD.
- Current Assignee Address: KR Seoul
- Agency: Fenwick & West LLP
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@3782d4b7
- Main IPC: G06K9/40
- IPC: G06K9/40 ; G06F16/532 ; G06T7/246 ; G06T1/20 ; G06T1/00 ; G06F16/51 ; G06T11/00 ; G06N3/02 ; G06N3/04 ; G06N3/08

Abstract:
A generative adversarial networks-based or GAN-based method for learning cross-domain relations is disclosed. A provided architecture includes two coupled GANs: a first GAN learning a translation of images from domain A to domain B, and a second GAN learning a translation of images from domain B to domain A. A loop formed by the first GAN and the second GAN causes sample images to be reconstructed into an original domain after being translated into a target domain. Therefore, loss functions representing reconstruction losses of the images may be used to train generative models.
Public/Granted literature
- US20190205334A1 METHOD FOR LEARNING CROSS-DOMAIN RELATIONS BASED ON GENERATIVE ADVERSARIAL NETWORKS Public/Granted day:2019-07-04
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