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[bibtex]@InProceedings{Tseng_2025_WACV, author = {Tseng, Yu-Yun and Sharma, Tanusree and Zhang, Lotus and Stangl, Abigale and Findlater, Leah and Wang, Yang and Gurari, Danna}, title = {BIV-Priv-Seg: Locating Private Content in Images Taken by People with Visual Impairments}, booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)}, month = {February}, year = {2025}, pages = {430-440} }
BIV-Priv-Seg: Locating Private Content in Images Taken by People with Visual Impairments
Abstract
Individuals who are blind or have low vision (BLV) are at a heightened risk of sharing private information if they share photographs they have taken. To facilitate developing technologies that can help them preserve privacy we introduce BIV-Priv-Seg the first localization dataset originating from people with visual impairments that shows private content. It contains 1028 images with segmentation annotations for 16 private object categories. We first characterize BIV-Priv-Seg and then evaluate modern models' performance for locating private content in the dataset. We find modern models struggle most with locating private objects that are not salient small and lack text as well as recognizing when private content is absent from an image. We facilitate future extensions by sharing our new dataset with the evaluation server at https://vizwiz.org/tasks-and-datasets/object-localization/.
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