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Comic strips are a popular and expressive form of visual storytelling thatcan convey humor, emotion, and information. However, they are inaccessible tothe BLV (Blind or Low Vision) community, who cannot perceive the images,layouts, and text of comics. Our goal in this paper is to create naturallanguage descriptions of comic strips that are accessible to the visuallyimpaired community. Our method consists of two steps: first, we use computervision techniques to extract information about the panels, characters, and textof the comic images; second, we use this information as additional context toprompt a multimodal large language model (MLLM) to produce the descriptions. Wetest our method on a collection of comics that have been annotated by humanexperts and measure its performance using both quantitative and qualitativemetrics. The outcomes of our experiments are encouraging and promising.

Comics for Everyone: Generating Accessible Text Descriptions for Comic Strips