Affiliation:
1. School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China
2. State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation Chinese Academy of Sciences Beijing China
3. College of Aerospace Technology and Engineering National University of Defense Technology Changsha China
Abstract
AbstractAs an amalgamation of landscape design and ichthyology, aquascape endeavors to create visually captivating aquatic environments imbued with artistic allure. Traditional methodologies in aquascape, governed by rigid principles such as composition and color coordination, may inadvertently curtail the aesthetic potential of the landscapes. In this paper, we propose Aquascape Generation based on Stable Diffusion Models (AG‐SDM), prioritizing aesthetic principles and color coordination to offer guiding principles for real artists in Aquascape creation. We meticulously curated and annotated three aquascape datasets with varying aspect ratios to accommodate diverse landscape design requirements regarding dimensions and proportions. Leveraging the Fréchet Inception Distance (FID) metric, we trained AGFID for quality assessment. Extensive experiments validate that our AG‐SDM excels in generating hyper‐realistic underwater landscape images, closely resembling real flora, and achieves state‐of‐the‐art performance in aquascape image generation.
Funder
National Natural Science Foundation of China
Beijing Natural Science Foundation
Natural Science Foundation of Beijing Municipality
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