Abstract: Highlights•Formulate point localization as a noise-to-point denoising process.•Eliminate reliance on heuristic priors, boosting efficiency and adaptability.•Pioneer the use of diffusion models for crowd localization frameworks.•Design a robust feature interpolation method in noisy scenes by differential attention.•Achieve competitive accuracy and flexibility across five benchmark datasets.
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