August 24, 2025SensorsOpen Access

ADBM: Adversarial Diffusion Bridge Model for Denoising of 3D Point Cloud Data

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Observational analysis improved 3D point cloud denoising using adversarial and diffusion methods, indicating enhanced restoration quality.

ADBM achieves improved denoising of 3D point clouds, enhancing local detail recovery under severe noise conditions.
Key metrics like Chamfer distance show significant improvement in reconstruction quality compared to baseline methods.
The approach integrates adversarial learning with diffusion models to guide the denoising process effectively.
Adversarial supervision enhances perceptual realism, making ADBM a promising method for robust point cloud restoration.

nam et al. (2025) studied this question.

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Observational analysis improved 3D point cloud denoising using adversarial and diffusion methods, indicating enhanced restoration quality.