Show simple item record

dc.contributor.authorZhou, Bolei
dc.contributor.authorZhao, Hang
dc.contributor.authorPuig Fernandez, Francesco Xavier
dc.contributor.authorFidler, Sanja
dc.contributor.authorBarriuso, Adela
dc.contributor.authorTorralba, Antonio
dc.date.accessioned2020-05-01T19:13:16Z
dc.date.available2020-05-01T19:13:16Z
dc.date.issued2017
dc.date.submitted2017-12
dc.identifier.isbn978-1-5386-0457-1
dc.identifier.urihttps://hdl.handle.net/1721.1/124982
dc.description.abstractScene parsing, or recognizing and segmenting objects and stuff in an image, is one of the key problems in computer vision. Despite the community's efforts in data collection, there are still few image datasets covering a wide range of scenes and object categories with dense and detailed annotations for scene parsing. In this paper, we introduce and analyze the ADE20K dataset, spanning diverse annotations of scenes, objects, parts of objects, and in some cases even parts of parts. A scene parsing benchmark is built upon the ADE20K with 150 object and stuff classes included. Several segmentation baseline models are evaluated on the benchmark. A novel network design called Cascade Segmentation Module is proposed to parse a scene into stuff, objects, and object parts in a cascade and improve over the baselines. We further show that the trained scene parsing networks can lead to applications such as image content removal and scene synthesis. ©2017 Paper presented at the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), July 21-26, 2017, Honolulu, Hawaii.en_US
dc.description.sponsorshipNSF (grant no. 1524817)en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/CVPR.2017.544en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleScene parsing through ADE20K dataseten_US
dc.typeArticleen_US
dc.identifier.citationZhou, Bolei, et al., "Scene parsing through ADE20K dataset." Proceedings, 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Piscataway, N.J.: IEEE, 2017): p. 5122-30 doi 10.1109/CVPR.2017.544 ©2017 Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalProceedings, 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-07-11T16:46:10Z
dspace.date.submission2019-07-11T16:46:11Z


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record