Literature Reviews
Reviewed research papers, articles, and publications relevant to digital accessibility.
5 results found tagged image captioning.
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"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models
Garg and colleagues investigate how well Vision-Language Models (VLMs) caption product images taken by blind and low-vision (BLV) people — a high-stakes everyday task that increasingly depends on tools like Be My AI, Microsoft Seeing AI, and general-…
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Multi-Perspective Visual Contrastive Decoding for Reliable Assistance
This technical paper presents MPVCD (Multi-Perspective Visual Contrastive Decoding), a framework designed to address the reliability of AI-generated visual descriptions for people who are blind or have low vision (BLV). The core problem it tackles: w…
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Accessify: An ML Powered Application to Provide Accessible Images on Web Sites
This demonstration paper presents Accessify, a browser plugin that uses machine learning to automatically generate alternative text descriptions for all images on a website, injecting them into the page’s DOM so screen readers can access them. The sy…
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Going Beyond One-Size-Fits-All Image Descriptions to Satisfy the Information Wants of People Who are Blind or Have Low Vision
Current image description practices typically produce a single, one-size-fits-all description for each image, yet the same image can appear across vastly different contexts — news websites, e-commerce platforms, social media feeds, travel sites, and …
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VisualAid: Enhancing Accessibility for Visually Impaired Users Through AI
This technical note presents VisualAid, an AI-powered Android application designed to help visually impaired users understand and navigate their physical surroundings. The app integrates multiple AI technologies into a single mobile interface: YOLO11…