References & Citations
Computer Science > Computer Vision and Pattern Recognition
Title: DALLE-URBAN: Capturing the urban design expertise of large text to image transformers
(Submitted on 3 Aug 2022 (v1), last revised 3 Oct 2022 (this version, v2))
Abstract: Automatically converting text descriptions into images using transformer architectures has recently received considerable attention. Such advances have implications for many applied design disciplines across fashion, art, architecture, urban planning, landscape design and the future tools available to such disciplines. However, a detailed analysis capturing the capabilities of such models, specifically with a focus on the built environment, has not been performed to date. In this work, we investigate the capabilities and biases of such text-to-image methods as it applies to the built environment in detail. We use a systematic grammar to generate queries related to the built environment and evaluate resulting generated images. We generate 1020 different images and find that text to image transformers are robust at generating realistic images across different domains for this use-case. Generated imagery can be found at the github: this https URL
Submission history
From: Sachith Seneviratne PhD [view email][v1] Wed, 3 Aug 2022 04:59:16 GMT (8279kb,D)
[v2] Mon, 3 Oct 2022 08:21:46 GMT (8323kb,D)
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