AI RESEARCH
RSGen: Enhancing Layout-Driven Remote Sensing Image Generation with Diverse Edge Guidance
arXiv CS.AI
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ArXi:2603.15484v1 Announce Type: cross Diffusion models have significantly mitigated the impact of annotated data scarcity in remote sensing (RS). Although recent approaches have successfully harnessed these models to enable diverse and controllable Layout-to-Image (L2I) synthesis, they still suffer from limited fine-grained control and fail to strictly adhere to bounding box constraints. To address these limitations, we propose RSGen, a plug-and-play framework that leverages diverse edge guidance to enhance layout-driven RS image generation.