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Context-Preserving Content Replacement for Privacy Protection in Screen Sharing with Generative AI

Year: 2025

Type: conference-paper

Abstract: a method for replacing private screen information with visually natural, context-preserving content.Image regions are replaced using generative AI, while text and icons are replaced using curated datasets, allowing tailored obfuscation based on content type.This method introduces a novel direction for protecting privacy during screen sharing, balancing effectiveness with viewing experience.

Source: ACM Symposium on User Interface Software and Technology (UIST)

DOI: 10.1145/3746058.3758442

Authors: Rimi Makita, Kaori Ikematsu, Yuki Igarashi

Institution: Ochanomizu University

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W7084096708

FWCI:

Cites: 11

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