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Conference Paper: Semantic segmentation with object clique potential

TitleSemantic segmentation with object clique potential
Authors
Issue Date2015
Citation
Proceedings of the IEEE International Conference on Computer Vision, 2015, v. 2015 International Conference on Computer Vision, ICCV 2015, p. 2587-2595 How to Cite?
Abstract© 2015 IEEE. We propose an object clique potential for semantic segmentation. Our object clique potential addresses the misclassified object-part issues arising in solutions based on fully-convolutional networks. Our object clique set, compared to that yielded from segment-proposal-based approaches, is with a significantly smaller size, making our method consume notably less computation. Regarding system design and model formation, our object clique potential can be regarded as a functional complement to local-appearance-based CRF models and works in synergy with these effective approaches for further performance improvement. Extensive experiments verify our method.
Persistent Identifierhttp://hdl.handle.net/10722/281937
ISSN

 

DC FieldValueLanguage
dc.contributor.authorQi, Xiaojuan-
dc.contributor.authorShi, Jianping-
dc.contributor.authorLiu, Shu-
dc.contributor.authorLiao, Renjie-
dc.contributor.authorJia, Jiaya-
dc.date.accessioned2020-04-09T09:19:09Z-
dc.date.available2020-04-09T09:19:09Z-
dc.date.issued2015-
dc.identifier.citationProceedings of the IEEE International Conference on Computer Vision, 2015, v. 2015 International Conference on Computer Vision, ICCV 2015, p. 2587-2595-
dc.identifier.issn1550-5499-
dc.identifier.urihttp://hdl.handle.net/10722/281937-
dc.description.abstract© 2015 IEEE. We propose an object clique potential for semantic segmentation. Our object clique potential addresses the misclassified object-part issues arising in solutions based on fully-convolutional networks. Our object clique set, compared to that yielded from segment-proposal-based approaches, is with a significantly smaller size, making our method consume notably less computation. Regarding system design and model formation, our object clique potential can be regarded as a functional complement to local-appearance-based CRF models and works in synergy with these effective approaches for further performance improvement. Extensive experiments verify our method.-
dc.languageeng-
dc.relation.ispartofProceedings of the IEEE International Conference on Computer Vision-
dc.titleSemantic segmentation with object clique potential-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICCV.2015.297-
dc.identifier.scopuseid_2-s2.0-84973867110-
dc.identifier.volume2015 International Conference on Computer Vision, ICCV 2015-
dc.identifier.spage2587-
dc.identifier.epage2595-

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