Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance

Published in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2024

Overview

Research on improving point cloud completion tasks through novel loss function design.

Description
Visualization of ShapeNet-55 benchmark. Gray represents the partial input. Yellow represents HyperCD. Green represents Landau CD (our novel approach)

Key Contributions

  • Proposed a novel chamfer distance loss function (based on Landau distribution) for point cloud completion task
  • Achieved new state-of-the-art results on some benchmark datasets

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