Transformer-guided denoising diffusion probabilistic model (DDPM) for flow field super-resolution (IMAGE)
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A novel FlowViT-Diff framework that integrates a Vision Transformer (ViT) with an enhanced denoising diffusion probabilistic model (DDPM) for super-resolution reconstruction of high-resolution flow fields from low-resolution inputs. In this framework, the ViT’s results serve as a prior to guide the DDPM during reconstruction, enabling high-fidelity recovery of both global structures and local details. This approach effectively addresses the limitations of conventional methods in capturing localized flow features.
Credit
Chinese Journal of Aeronautics
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