Personal AI Agent for Camera Roll VQA
This paper introduces the personal camera roll visual question answering task, constructs the camroll dataset with 50 users, 31,476 images, and 2,500 QA pairs, and designs camroll-agent, a conversational AI agent with hierarchical memory and efficient tools. Experiments show it outperforms baselines, highlighting the need for specialized approaches to personalized visual memory.
[2606.05275] Personal AI Agent for Camera Roll VQA
[Submitted on 3 Jun 2026]
Title:Personal AI Agent for Camera Roll VQA
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Abstract:We study the personal camera roll visual question answering setting. In this setting, a conversational AI assistant can access a user's personal camera roll and retrieve relevant photos to answer queries, ranging from simple factual questions (e.g., `Name of the food I tried yesterday?'') to more open-ended ones (e.g., `Recommend some dishes I have never eaten before''). Given the vast nature of the personal camera roll (i.e., multiple years, hundreds to thousands of photos), a successful AI assistant needs to understand a long-horizon, highly personalized visual content stream in order to navigate and locate the correct and/or relevant information. To support this, we collect and manually annotate questions that mimic real-world usage. The final dataset, camroll, contains 50 users, 31,476 images, and 2,500 QA pairs. We further design camroll-agent, a conversational AI agent equipped with hierarchical memory and a minimal set of tools for efficient navigation over large, personalized visual memory. Experimental results show that camroll-agent outperforms numerous baselines and methods for long-context understanding AI agents system. Together, the camroll dataset and camroll-agent highlight the gap in AI agents' long-context reasoning: personalized visual memory requires different approaches from standard long-context textual memory, especially when consistency, visual details, and user-specific context are present.
Comments: Project page, code, and demo: this https URL
Subjects:
Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI)
Cite as: arXiv:2606.05275 [cs.CV]
(or arXiv:2606.05275v1 [cs.CV] for this version)
https://doi.org/10.48550/arXiv.2606.05275
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Thao Nguyen [view email] [v1] Wed, 3 Jun 2026 17:59:30 UTC (1,544 KB)
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