  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 preserve privacy, we introduce
BIV-Priv-Seg, the first localization dataset originating from people with
visual impairments that shows private content. It contains 1,028 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.
