Coherence-Oriented Dream Scene Visualisation

Abstract:Dreams can be emotionally intense but difficult to communicate. We describe the Dream Scene Visualiser (DSV) system which turns written dream descriptions into a temporal sequence of four panel images visualising the dream. This starts with a large language model prompted to split a dream description into four chronological parts. Then a text-to-image model produces images for each part with visual coherence maintained across the sequence, and DSV regenerates any image not suitably matching the text. We evaluate DSV over 50 visualisations from dream descriptions in DreamBank, and report quality, fidelity and coherence results via objective measures employing the CLIP, DINOv2 and Qwen2-VL vision-language models.

Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV)

arXiv:2608.05233 [cs.AI]

(or arXiv:2608.05233v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.05233 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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