Cross-Modal Scene Networks

dc.contributor.authorAytar, Yusuf
dc.contributor.authorCastrejon, Lluis
dc.contributor.authorVondrick, Carl
dc.contributor.authorPirsiavash, Hamed
dc.contributor.authorTorralba, Antonio
dc.date.accessioned2019-07-03T13:33:32Z
dc.date.available2019-07-03T13:33:32Z
dc.date.issued2017-09-18
dc.description.abstractPeople can recognize scenes across many different modalities beyond natural images. In this paper, we investigate how to learn cross-modal scene representations that transfer across modalities. To study this problem, we introduce a new cross-modal scene dataset. While convolutional neural networks can categorize scenes well, they also learn an intermediate representation not aligned across modalities, which is undesirable for cross-modal transfer applications. We present methods to regularize cross-modal convolutional neural networks so that they have a shared representation that is agnostic of the modality. Our experiments suggest that our scene representation can help transfer representations across modalities for retrieval. Moreover, our visualizations suggest that units emerge in the shared representation that tend to activate on consistent concepts independently of the modality.en_US
dc.description.sponsorshipThis work was supported by NSF grant IIS-1524817, by a Google faculty research award to A.T and by a Google Ph.D. fellowship to C.V.en_US
dc.description.urihttps://ieeexplore.ieee.org/abstract/document/8039215en_US
dc.format.extent12 pagesen_US
dc.genrejournal articles preprintsen_US
dc.identifierdoi:10.13016/m2r4pl-lmzf
dc.identifier.citationYusuf Aytar, et.al, Cross-Modal Scene Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 40 , Issue: 10 , Oct. 1 2018 , DOI: 10.1109/TPAMI.2017.2753232en_US
dc.identifier.urihttps://doi.org/10.1109/TPAMI.2017.2753232
dc.identifier.urihttp://hdl.handle.net/11603/14333
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights© 2017 IEEE
dc.subjectcross-modal perceptionen_US
dc.subjectdomain adaptationen_US
dc.subjectscene understandingen_US
dc.titleCross-Modal Scene Networksen_US
dc.typeTexten_US

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