E-Bridge approximates low-cost geodesic trajectories in diffusion bridges for image restoration by using shorter time horizons, entropy-regularized starts mixing degraded images with noise, and consistency-model single-step mapping, achieving SOTA results with one or few steps.
To find the optimal trajectoryµ(t) =E[X t]that coincides with this geodesic, we analyze the energy required to traverse the displacement
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Energy-oriented Diffusion Bridge for Image Restoration with Foundational Diffusion Models
E-Bridge approximates low-cost geodesic trajectories in diffusion bridges for image restoration by using shorter time horizons, entropy-regularized starts mixing degraded images with noise, and consistency-model single-step mapping, achieving SOTA results with one or few steps.