Show simple item record

dc.contributor.authorPatterson, Genevieve
dc.contributor.authorXiao, Jianxiong
dc.contributor.authorHays, James
dc.contributor.authorRussell, Bryan Christopher
dc.contributor.authorEhinger, Krista A
dc.contributor.authorTorralba, Antonio
dc.contributor.authorOliva, Aude
dc.date.accessioned2018-06-18T15:51:59Z
dc.date.available2018-06-18T15:51:59Z
dc.date.issued2013-08
dc.identifier.issn1664-1078
dc.identifier.urihttp://hdl.handle.net/1721.1/116359
dc.description.abstractA longstanding goal of computer vision is to build a system that can automatically understand a 3D scene from a single image. This requires extracting semantic concepts and 3D information from 2D images which can depict an enormous variety of environments that comprise our visual world. This paper summarizes our recent efforts toward these goals. First, we describe the richly annotated SUN database which is a collection of annotated images spanning 908 different scene categories with object, attribute, and geometric labels for many scenes. This database allows us to systematically study the space of scenes and to establish a benchmark for scene and object recognition. We augment the categorical SUN database with 102 scene attributes for every image and explore attribute recognition. Finally, we present an integrated system to extract the 3D structure of the scene and objects depicted in an image.en_US
dc.description.sponsorshipGoogle U.S./Canada Ph.D. Fellowship in Computer Visionen_US
dc.description.sponsorshipNational Science Foundation (U.S.) (grant 1016862)en_US
dc.description.sponsorshipGoogle Faculty Research Awarden_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Career Award 1149853)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Career Award 0747120)en_US
dc.description.sponsorshipUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (N000141010933)en_US
dc.publisherFrontiers Media SAen_US
dc.relation.isversionofhttp://dx.doi.org/10.3389/FPSYG.2013.00506en_US
dc.rightsCreative Commons Attribution 4.0 International Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceFrontiersen_US
dc.subjectSUN database, basic level scene understanding, scene recognition, scene attributes, geometry recognition, 3D contexten_US
dc.titleBasic level scene understanding: categories, attributes and structuresen_US
dc.typeArticleen_US
dc.identifier.citationXiao, Jianxiong, James Hays, Bryan C. Russell, Genevieve Patterson, Krista A. Ehinger, Antonio Torralba, and Aude Oliva. “Basic Level Scene Understanding: Categories, Attributes and Structures.” Frontiers in Psychology 4 (2013).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorXiao, Jianxiong
dc.contributor.mitauthorHays, James
dc.contributor.mitauthorRussell, Bryan Christopher
dc.contributor.mitauthorEhinger, Krista A
dc.contributor.mitauthorTorralba, Antonio
dc.contributor.mitauthorOliva, Aude
dc.relation.journalFrontiers in Psychologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-05-11T13:21:26Z
dspace.orderedauthorsXiao, Jianxiong; Hays, James; Russell, Bryan C.; Patterson, Genevieve; Ehinger, Krista A.; Torralba, Antonio; Oliva, Audeen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-4915-0256
mit.licensePUBLISHER_CCen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record