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dc.contributor.authorSanturkar, Shibani (Shibani Vinay)
dc.contributor.authorBudden, David
dc.contributor.authorShavit, Nir N.
dc.date.accessioned2020-06-19T14:40:37Z
dc.date.available2020-06-19T14:40:37Z
dc.date.issued2018-09
dc.identifier.isbn978-1-5386-4160-6
dc.identifier.isbn978-1-5386-4159-0
dc.identifier.isbn978-1-5386-4161-3
dc.identifier.issn2472-7822
dc.identifier.urihttps://hdl.handle.net/1721.1/125883
dc.description.abstractTraditional image and video compression algorithms rely on hand-crafted encoder/decoder pairs (codecs) that lack adaptability and are agnostic to the data being compressed. We describe the concept of generative compression, the compression of data using generative models, and suggest that it is a direction worth pursuing to produce more accurate and visually pleasing reconstructions at deeper compression levels for both image and video data. We also show that generative compression is orders- of-magnitude more robust to bit errors (e.g., from noisy channels) than traditional variable-length coding schemes.en_US
dc.description.sponsorshipNational Science Foundation (NSF) (Grant CCF-1563880)en_US
dc.description.sponsorshipNational Science Foundation (NSF) (Grant IIS-1447786)en_US
dc.description.sponsorshipIntelligence Advanced Research Projects Activity (IARPA) (Grant 138076-5093555)en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/PCS.2018.8456298en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleGenerative Compressionen_US
dc.typeArticleen_US
dc.identifier.citationS. Santurkar, D. Budden and N. Shavit, "Generative Compression," 2018 Picture Coding Symposium (PCS), San Francisco, CA, 2018, pp. 258-262, doi: 10.1109/PCS.2018.8456298.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journal2018 Picture Coding Symposium (PCS)en_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-07-03T12:54:31Z
dspace.date.submission2019-07-03T12:54:32Z
mit.metadata.statusComplete


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