cVIL: Class-Centric Visual Interactive Labeling

dc.contributor.authorMatt, Matthiasen_US
dc.contributor.authorZeppelzauer, Matthiasen_US
dc.contributor.authorWaldner, Manuelaen_US
dc.contributor.editorEl-Assady, Mennatallahen_US
dc.contributor.editorSchulz, Hans-Jörgen_US
dc.date.accessioned2024-05-21T08:29:47Z
dc.date.available2024-05-21T08:29:47Z
dc.date.issued2024
dc.description.abstractWe present cVIL, a class-centric approach to visual interactive labeling, which facilitates human annotation of large and complex image data sets. cVIL uses different property measures to support instance labeling for labeling difficult instances and batch labeling to quickly label easy instances. Simulated experiments reveal that cVIL with batch labeling can outperform traditional labeling approaches based on active learning. In a user study, cVIL led to better accuracy and higher user preference compared to a traditional instance-based visual interactive labeling approach based on 2D scatterplots.en_US
dc.description.sectionheadersBest Paper Award
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.identifier.doi10.2312/eurova.20241113
dc.identifier.isbn978-3-03868-253-0
dc.identifier.pages6 pages
dc.identifier.urihttps://doi.org/10.2312/eurova.20241113
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/eurova20241113
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing → Visual analytics; User interface design
dc.subjectHuman centered computing → Visual analytics
dc.subjectUser interface design
dc.titlecVIL: Class-Centric Visual Interactive Labelingen_US
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