# Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users

arXiv: https://arxiv.org/abs/2102.00576 · HTML: https://mlsanity.com/paper/2102.00576/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Feb 2021.

## Built on by (most cited first, 4 of 4)

- [More than One Step at a Time: Designing Procedural Feedback for Non-visual Makeup Routines](https://mlsanity.com/paper/2507.03942/) (2025)
- [Finding the Signal in the Noise: An Exploratory Study on Assessing the Effectiveness of AI and Accessibility Forums for Blind Users' Support Needs](https://mlsanity.com/paper/2602.18623/) (2026)
- [SweeperBot: Making 3D Browsing Accessible through View Analysis and Visual Question Answering](https://mlsanity.com/paper/2511.14567/) (2025)
- [Generative UI as an Accessibility Bridge: Lessons from C2C E-Commerce](https://mlsanity.com/paper/2604.25455/) (2026)

## Abstract (arXiv)

Online shopping has become a valuable modern convenience, but blind or low vision (BLV) users still face significant challenges using it, because of: 1) inadequate image descriptions and 2) the inability to filter large amounts of information using screen readers. To address those challenges, we propose Revamp, a system that leverages customer reviews for interactive information retrieval. Revamp is a browser integration that supports review-based question-answering interactions on a reconstructed product page. From our interview, we identified four main aspects (color, logo, shape, and size) that are vital for BLV users to understand the visual appearance of a product. Based on the findings, we formulated syntactic rules to extract review snippets, which were used to generate image descriptions and responses to users' queries. Evaluations with eight BLV users showed that Revamp 1) provided useful descriptive information for understanding product appearance and 2) helped the participants locate key information efficiently.