  Privacy policies have become the most critical approach to safeguarding
individuals' privacy and digital security. To enhance their presentation and
readability, researchers propose the concept of contextual privacy policies
(CPPs), aiming to fragment policies into shorter snippets and display them only
in corresponding contexts. In this paper, we propose a novel multi-modal
framework, namely SeePrivacy, designed to automatically generate contextual
privacy policies for mobile apps. Our method synergistically combines mobile
GUI understanding and privacy policy document analysis, yielding an impressive
overall 83.6% coverage rate for privacy-related context detection and an
accuracy of 0.92 in extracting corresponding policy segments. Remarkably, 96%
of the retrieved policy segments can be correctly matched with their contexts.
The user study shows SeePrivacy demonstrates excellent functionality and
usability (4.5/5). Specifically, participants exhibit a greater willingness to
read CPPs (4.1/5) compared to original privacy policies (2/5). Our solution
effectively assists users in comprehending privacy notices, and this research
establishes a solid foundation for further advancements and exploration.
