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This research aims to enhance image captioning for Arabic using the BLIP-2 model, addressing language-specific challenges.

March 29, 2026Applied SciencesOpen Access

Image Captioning Through Deep Learning: An Adaptation of the BLIP-2 Model to Arabic

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This research aims to enhance image captioning for Arabic using the BLIP-2 model, addressing language-specific challenges.
Adapting the BLIP-2 model for Arabic language.
Utilizing machine-translated datasets like Flickr 30k.
Incorporating a vision transformer for image encoding and CamelBERT for text generation.
Using a Querying Transformer to improve cross-modal alignment.
Demonstrated the potential of the BLIP-2 model in generating coherent Arabic captions.
Overcame challenges such as translation artifacts and linguistic complexities.
Showed promising results despite limitations in Arabic datasets.

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Image captioning generates textual descriptions in Arabic, suggesting advances in multilingual artificial intelligence.

Abdelaal et al. (2026) studied this question.

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