[IPOL discuss] [IPOL announce] new article: Latent Diffusion Approaches for Conditional Generation of Aerial Imagery: A Study

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2025/580/

Roger Marí, and Rafael Redondo,
Latent Diffusion Approaches for Conditional Generation of Aerial 
Imagery: A Study,
Image Processing On Line, 15 (2025), pp. 20–31.
https://doi.org/10.5201/ipol.2025.580

Abstract
Generative artificial intelligence is increasingly being applied in 
diverse areas such as architecture design, music composition, or 
character animation. Among the generative methods, diffusion models are 
today the state of the art in the synthesis of high quality images with 
inherent diversity and realism. This paper aims to evaluate the fidelity 
and realism of the synthesis achieved by different architectural 
variations of a latent diffusion model, which is used to generate aerial 
images conditioned to semantic maps. As shown in the results, the 
diffusion model tends to correctly capture the overall semantic 
structure and generates realistic textures, often with a lack of 
fine-grained detail. Among the conditioning variations, cross-attention 
layers were crucial to outline the semantic segments more accurately and 
exploit conditional data more effectively.




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