cVIL: Class-Centric Visual Interactive Labeling
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913350172016640 |
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| author | Matt, Matthias Zeppelzauer, Matthias Waldner, Manuela |
| author_facet | Matt, Matthias Zeppelzauer, Matthias Waldner, Manuela |
| contents | We 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_08150 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | cVIL: Class-Centric Visual Interactive Labeling Matt, Matthias Zeppelzauer, Matthias Waldner, Manuela Human-Computer Interaction We 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. |
| title | cVIL: Class-Centric Visual Interactive Labeling |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2405.08150 |