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dc.contributor.authorVondrick, Carl
dc.contributor.authorPirsiavash, Hamed
dc.contributor.authorTorralba, Antonio
dc.date.accessioned2020-04-08T17:36:58Z
dc.date.available2020-04-08T17:36:58Z
dc.date.issued2016
dc.date.submitted2016-12
dc.identifier.urihttps://hdl.handle.net/1721.1/124545
dc.description.abstractWe capitalize on large amounts of unlabeled video in order to learn a model of scene dynamics for both video recognition tasks (e.g. action classification) and video generation tasks (e.g. future prediction). We propose a generative adversarial network for video with a spatio-temporal convolutional architecture that untangles the scene's foreground from the background. Experiments suggest this model can generate tiny videos up to a second at full frame rate better than simple baselines, and we show its utility at predicting plausible futures of static images. Moreover, experiments and visualizations show the model internally learns useful features for recognizing actions with minimal supervision, suggesting scene dynamics are a promising signal for representation learning. We believe generative video models can impact many applications in video understanding and simulation. ©2016 Presented at a poster session of the Conference on Neural Information Processing Systems (NIPS 2016), December 5-10, 2016, Barcelona, Spainen_US
dc.description.sponsorshipNSF (grant no. 1524817)en_US
dc.language.isoen
dc.relation.isversionofhttps://papers.nips.cc/paper/6194-generating-videos-with-scene-dynamicsen_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceNeural Information Processing Systems (NIPS)en_US
dc.titleGenerating videos with scene dynamicsen_US
dc.typeArticleen_US
dc.identifier.citationVondrick, Carl, Hamed Pirsiavash, and Antonio Torralba, "Generating videos with scene dynamics." Advances in Neural Information Processing Systems 29 (2016) url https://papers.nips.cc/paper/6194-generating-videos-with-scene-dynamics ©2016 Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalAdvances in Neural Information Processing Systemsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-07-11T16:00:10Z
dspace.date.submission2019-07-11T16:00:11Z
mit.journal.volume29en_US
mit.metadata.statusComplete


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