The access of visually impaired users to imagery in social media is constrained by the
availability of suitable alt text. It is unknown how imperfections in emerging tools for …

Evaluating the quality of accessible image captions with human raters is difficult, as it may
be difficult for a visually impaired user to know how comprehensive a caption is, whereas a …

AI image captioning challenges encourage broad participation in designing algorithms that
automatically create captions for a variety of images and users. To create large datasets …

We designed and deployed automatic alt-text (AAT), a system that applies computer vision
technology to identify faces, objects, and themes from photos to generate photo alt-text for …

Blind users rely on alternative text (alt-text) to understand an image; however, alt-text is often
missing. AI-generated captions are a more scalable alternative, but they often miss crucial …

Blind and low vision (BLV) creators use images to communicate with sighted audiences.
However, creating or retrieving images is challenging for BLV creators as it is difficult to use …

While an important problem in the vision community is to design algorithms that can
automatically caption images, few publicly-available datasets for algorithm development …

Accessing images online is often difficult for users with vision impairments. This population
relies on text descriptions of images that vary based on website authors' accessibility …

One of the ways blind people understand their surroundings is by clicking images and
relying on descriptions generated by image captioning systems. Current work on captioning …

Crowdsourcing plays a key role in developing algorithms for image recognition or
captioning. Major datasets, such as MS COCO or Flickr30K, have been built by eliciting …