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AssigneeAdobe Inc.
InventorsJohn Collomosse, Zhe Lin, Saeid Motiian, Hailin Jin, Baldo Faieta, Alex Filipkowski
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The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly identifying digital images with similar style to a query digital image using fine-grain style determination via weakly supervised style extraction neural networks. For example, the disclosed systems can extract a style embedding from a query digital image using a style extraction neural network such as a novel two-branch autoencoder architecture or a weakly supervised discriminative neural network. The disclosed systems can generate a combined style embedding by combining complementary style embeddings from different style extraction neural networks. Moreover, the disclosed systems can search a repository of digital images to identify digital images with similar style to the query digital image. The disclosed systems can also learn parameters for one or more style extraction neural network through weakly supervised training without a specifically labeled style ontology for sample digital images.
A non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause a computing device to:
A system comprising:
A computer-implemented method for searching digital image repositories to identify digital images with matching styles, the computer-implemented method comprising:
Dependencies are inferred from the claim text.