ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2505.14218
159
0

Flexible-weighted Chamfer Distance: Enhanced Objective Function for Point Cloud Completion

20 May 2025
Jie Li
Shengwei Tian
Long Yu
Xin Ning
ArXivPDFHTML
Abstract

Chamfer Distance (CD) comprises two components that can evaluate the global distribution and local performance of generated point clouds, making it widely utilized as a similarity measure between generated and target point clouds in point cloud completion tasks. Additionally, CD's computational efficiency has led to its frequent application as an objective function for guiding point cloud generation. However, using CD directly as an objective function with fixed equal weights for its two components can often result in seemingly high overall performance (i.e., low CD score), while failing to achieve a good global distribution. This is typically reflected in high Earth Mover's Distance (EMD) and Decomposed Chamfer Distance (DCD) scores, alongside poor human assessments. To address this issue, we propose a Flexible-Weighted Chamfer Distance (FCD) to guide point cloud generation. FCD assigns a higher weight to the global distribution component of CD and incorporates a flexible weighting strategy to adjust the balance between the two components, aiming to improve global distribution while maintaining robust overall performance. Experimental results on two state-of-the-art networks demonstrate that our method achieves superior results across multiple evaluation metrics, including CD, EMD, DCD, and F-Score, as well as in human evaluations.

View on arXiv
@article{li2025_2505.14218,
  title={ Flexible-weighted Chamfer Distance: Enhanced Objective Function for Point Cloud Completion },
  author={ Jie Li and Shengwei Tian and Long Yu and Xin Ning },
  journal={arXiv preprint arXiv:2505.14218},
  year={ 2025 }
}
Comments on this paper