DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, Deunsol | - |
dc.contributor.author | Kang, Dahyun | - |
dc.contributor.author | Kwak, Suha | - |
dc.contributor.author | Cho, Minsu | - |
dc.date.accessioned | 2023-01-09T02:40:12Z | - |
dc.date.available | 2023-01-09T02:40:12Z | - |
dc.date.created | 2023-01-06 | - |
dc.date.issued | 2022-12 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/114891 | - |
dc.description.abstract | Metric learning aims to build a distance metric typically by learning an effective embedding function that maps similar objects into nearby points in its embedding space. Despite recent advances in deep metric learning, it remains challenging for the learned metric to generalize to unseen classes with a substantial domain gap. To tackle the issue, we explore a new problem of few-shot metric learning that aims to adapt the embedding function to the target domain with only a few annotated data. We introduce three few-shot metric learning baselines and propose the Channel-Rectifier Meta-Learning (CRML), which effectively adapts the metric space online by adjusting channels of intermediate layers. Experimental analyses on miniImageNet, CUB-200-2011, MPII, as well as a new dataset, miniDeepFashion, demonstrate that our method consistently improves the learned metric by adapting it to target classes and achieves a greater gain in image retrieval when the domain gap from the source classes is larger. | - |
dc.language | English | - |
dc.publisher | Asian Conference on Computer Vision | - |
dc.relation.isPartOf | Asian Conference on Computer Vision 2022 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.title | Few-Shot Metric Learning: Online Adaptation of Embedding for Retrieval | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.identifier.bibliographicCitation | Asian Conference on Computer Vision 2022, pp.54 - 70 | - |
dc.citation.conferenceDate | 2022-12-04 | - |
dc.citation.conferencePlace | HK | - |
dc.citation.endPage | 70 | - |
dc.citation.startPage | 54 | - |
dc.citation.title | Asian Conference on Computer Vision 2022 | - |
dc.contributor.affiliatedAuthor | Jung, Deunsol | - |
dc.contributor.affiliatedAuthor | Kang, Dahyun | - |
dc.contributor.affiliatedAuthor | Kwak, Suha | - |
dc.contributor.affiliatedAuthor | Cho, Minsu | - |
dc.identifier.scopusid | 2-s2.0-85151052018 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
library@postech.ac.kr Tel: 054-279-2548
Copyrights © by 2017 Pohang University of Science ad Technology All right reserved.