Coloring with limited data: Few-shot colorization via memory augmented networks

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dc.contributor.authorYoo, Seungjooko
dc.contributor.authorBahng, Hyojinko
dc.contributor.authorChung, Sunghyoko
dc.contributor.authorLee, Junsooko
dc.contributor.authorChang, Jaehyukko
dc.contributor.authorChoo, Jaegulko
dc.date.accessioned2021-01-12T02:50:20Z-
dc.date.available2021-01-12T02:50:20Z-
dc.date.created2020-12-03-
dc.date.issued2019-06-
dc.identifier.citation32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019, pp.11275 - 11284-
dc.identifier.urihttp://hdl.handle.net/10203/279876-
dc.description.abstractDespite recent advancements in deep learning-based automatic colorization, they are still limited when it comes to few-shot learning. Existing models require a significant amount of training data. To tackle this issue, we present a novel memory-augmented colorization model MemoPainter that can produce high-quality colorization with limited data. In particular, our model is able to capture rare instances and successfully colorize them. Also, we propose a novel threshold triplet loss that enables unsupervised training of memory networks without the need for class labels. Experiments show that our model has superior quality in both few-shot and one-shot colorization tasks.-
dc.languageEnglish-
dc.publisherIEEE Computer Society-
dc.titleColoring with limited data: Few-shot colorization via memory augmented networks-
dc.typeConference-
dc.identifier.wosid000542649304090-
dc.identifier.scopusid2-s2.0-85078777565-
dc.type.rimsCONF-
dc.citation.beginningpage11275-
dc.citation.endingpage11284-
dc.citation.publicationname32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationLong Beach-
dc.identifier.doi10.1109/CVPR.2019.01154-
dc.contributor.localauthorChoo, Jaegul-
dc.contributor.nonIdAuthorYoo, Seungjoo-
dc.contributor.nonIdAuthorBahng, Hyojin-
dc.contributor.nonIdAuthorChung, Sunghyo-
dc.contributor.nonIdAuthorLee, Junsoo-
dc.contributor.nonIdAuthorChang, Jaehyuk-
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