Fine-tuning a latent diffusion model on 500 footprint-text-floorplan triples yields plausible floorplans for several building types, though the quantitative evaluation is weak and irreproducible.
Review of Large Vision Models and Visual Prompt Engineering
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abstract
Visual prompt engineering is a fundamental technology in the field of visual and image Artificial General Intelligence, serving as a key component for achieving zero-shot capabilities. As the development of large vision models progresses, the importance of prompt engineering becomes increasingly evident. Designing suitable prompts for specific visual tasks has emerged as a meaningful research direction. This review aims to summarize the methods employed in the computer vision domain for large vision models and visual prompt engineering, exploring the latest advancements in visual prompt engineering. We present influential large models in the visual domain and a range of prompt engineering methods employed on these models. It is our hope that this review provides a comprehensive and systematic description of prompt engineering methods based on large visual models, offering valuable insights for future researchers in their exploration of this field.
fields
cs.LG 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
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Generating floorplans for various building functionalities via latent diffusion model
Fine-tuning a latent diffusion model on 500 footprint-text-floorplan triples yields plausible floorplans for several building types, though the quantitative evaluation is weak and irreproducible.