OmniRSI: Taming Latent Diffusion for Unified Multimodal Remote Sensing Image Generation
Multimodal remote sensing image generation emerges as a promising paradigm for recovering complete and complementary observations from heterogeneous and partially observed remote sensing data. However, existing methods predominantly depend on sensor-specific fine-tuning of natural image generation models, limiting unified multimodal generation capacity due to the absence of shared representations and robust conditioning mechanisms. To address these challenges, we propose OmniRSI, a unified multimodal remote sensing image generation model. Specifically, we develop a remote sensing-specific variational autoencoder that captures multimodal priors and promotes a locally smooth latent space fo...
| Authors | Hebaixu Wang, Jing Zhang, Haonan Guo et al. |
|---|---|
| Primary category | cs.CV |
| Published | 11 October 2026 |
| Last updated at source | 11 October 2026 |
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