Publication: AIM 2022 challenge on instagram filter removal: Methods and results
dc.contributor.author | Kınlı, Osman Furkan | |
dc.contributor.author | Menteş, Sami | |
dc.contributor.author | Özcan, Barış | |
dc.contributor.author | Kıraç, Mustafa Furkan | |
dc.contributor.department | Computer Science | |
dc.contributor.ozuauthor | KINLI, Osman Furkan | |
dc.contributor.ozuauthor | KIRAÇ, Mustafa Furkan | |
dc.contributor.ozugradstudent | Menteş, Sami | |
dc.contributor.ozugradstudent | Özcan, Barış | |
dc.date.accessioned | 2024-01-24T11:43:34Z | |
dc.date.available | 2024-01-24T11:43:34Z | |
dc.date.issued | 2023 | |
dc.description.abstract | This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations, and the feature maps of the original content may be interpolated into a different domain. This reduces the overall performance of the recent deep learning strategies. The main goal of this challenge is to produce realistic and visually plausible images where the impact of the filters applied is mitigated while preserving the content. The proposed solutions are ranked in terms of the PSNR value with respect to the original images. There are two prior studies on this task as the baseline, and a total of 9 teams have competed in the final phase of the challenge. The comparison of qualitative results of the proposed solutions and the benchmark for the challenge are presented in this report. | en_US |
dc.description.sponsorship | Eidgenössische Technische Hochschule Zürich ; Julius-Maximilians-Universität Würzburg | |
dc.identifier.doi | 10.1007/978-3-031-25066-8_2 | en_US |
dc.identifier.endpage | 43 | en_US |
dc.identifier.isbn | 978-303125065-1 | |
dc.identifier.issn | 0302-9743 | en_US |
dc.identifier.scopus | 2-s2.0-85151163050 | |
dc.identifier.startpage | 27 | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/9091 | |
dc.identifier.uri | https://doi.org/10.1007/978-3-031-25066-8_2 | |
dc.identifier.volume | 13803 LNCS | en_US |
dc.language.iso | eng | en_US |
dc.publicationstatus | Published | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartof | ECCV 2022: Computer Vision – ECCV 2022 Workshops, Part of the Lecture Notes in Computer Science book series (LNCS,volume 13803) | |
dc.relation.publicationcategory | International | |
dc.rights | restrictedAccess | |
dc.subject.keywords | Filter removal | en_US |
dc.subject.keywords | Image restoration | en_US |
dc.subject.keywords | Image-to-image translation | en_US |
dc.title | AIM 2022 challenge on instagram filter removal: Methods and results | en_US |
dc.type | conferenceObject | en_US |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | 85662e71-2a61-492a-b407-df4d38ab90d7 | |
relation.isOrgUnitOfPublication.latestForDiscovery | 85662e71-2a61-492a-b407-df4d38ab90d7 |
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