Better matching of partial 3D point clouds by using uncertainty with UTOPIC

Better matching of partial 3D point clouds by using uncertainty with UTOPIC

UTOPIC: Uncertainty-aware Overlap Prediction Network for Partial Point Cloud Registration
arXiv paper abstract https://arxiv.org/abs/2208.02712v1
arXiv PDF paper https://arxiv.org/pdf/2208.02712v1.pdf
GitHub https://github.com/zhileichen99/utopic

High-confidence overlap prediction and accurate correspondences are critical for cutting-edge models to align paired point clouds in a partial-to-partial manner.

However, there inherently exists uncertainty between the overlapping and non-overlapping regions, which has always been neglected

… propose a novel uncertainty-aware overlap prediction network, dubbed UTOPIC, to tackle the ambiguous overlap prediction problem

… induce the feature extractor to implicitly perceive the shape knowledge through a completion decoder, and present a geometric relation embedding for Transformer to obtain transformation-invariant geometry-aware feature representations.

… UTOPIC can achieve stable and accurate registration results, even for the inputs with limited overlapping areas.

… demonstrate the superiority of … approach over state-of-the-art methods …

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I apply innovative technologies like machine learning, computer vision, and physics to further an organization's goals. Am recognized innovator with 66 patents.