Lune

UIST2025顶会

Imago Obscura: An Image Privacy AI Co-pilot to Enable Identification and Mitigation of Risks

Kyzyl Monteiro, Yuchen Wu, Sauvik Das

2025年份
2被引次数
6顶会引用

摘要

Users often struggle to navigate the privacy / publicity boundary in sharing images online: they may lack awareness of image privacy risks or the ability to apply effective mitigation strategies. To address this challenge, we introduce and evaluate Imago Obscura, an intent-aware AI-powered image-editing copilot that enables users to identify and mitigate privacy risks in images they intend to share. Driven by design requirements from a formative user study with 7 image-editing experts, Imago Obscura enables users to articulate their image-sharing intent and privacy concerns. The system uses these inputs to surface contextually pertinent privacy risks, and then recommends and facilitates application of a suite of obfuscation techniques found to be effective in prior literature — e.g., inpainting, blurring, and generative content replacement. We evaluated Imago Obscura with 15 end-users in a lab study and found that it improved users’ awareness of image privacy risks and their ability to address them, enabling more informed sharing decisions.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper6

问问它们各自怎么用它

它引用的顶会 Paper19

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖