DiffSAC uses diffusion models to guide robust estimation sampling
zhenjun_zhao · x · 2026-09-01
To address inefficient sampling in traditional robust estimation, DiffSAC introduces a diffusion model to learn the distribution of effective minimal sample sets. It refines confidence for each data point, drastically reducing the processing of bad sets. DiffSAC achieves state-of-the-art performance with only dozens of hypothesis evaluations, significantly boosting efficiency across multiple computer vision tasks.
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