FEW-SHOT DOMAIN ADAPTATION IN GENERATIVE ADVERSARIAL NETWORKS

FEW-SHOT DOMAIN ADAPTATION IN GENERATIVE ADVERSARIAL NETWORKS

The present disclosure provides improved methods for learning a generative model with limited training data, by leveraging a pre-trained GAN model from a related domain and adapting it to the new domain given a set of target examples from the new or target domain.

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Bibliographische Detailangaben
Hauptverfasser: CHU, Wen-Sheng, KUMAR, Abhishek, ROBB, Esther
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Beschreibung
Zusammenfassung:The present disclosure provides improved methods for learning a generative model with limited training data, by leveraging a pre-trained GAN model from a related domain and adapting it to the new domain given a set of target examples from the new or target domain.