Multi-stage refinement network for point cloud completion based on geodesic attention
Abstract The attention mechanism has significantly progressed in various point cloud tasks. Benefiting from its significant competence in capturing long-range dependencies, research in point cloud completion has achieved promising results. However, the typically disordered point cloud data features...
Saved in:
Main Authors: | Yuchen Chang, Kaiping Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-86704-6 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hybrid Offset Position Encoding for Large-Scale Point Cloud Semantic Segmentation
by: Yu Xiao, et al.
Published: (2025-01-01) -
A Few-Shot Knowledge Graph Completion Model With Neighbor Filter and Affine Attention
by: Hongfang Gong, et al.
Published: (2025-01-01) -
Completeness of certain compact Lorentzian locally symmetric spaces
by: Leistner, Thomas, et al.
Published: (2023-05-01) -
Hybrid Method for Point Cloud Classification
by: Abdurrahman Hazer, et al.
Published: (2025-01-01) -
Differential of the Stretch Tensor for Any Dimension with Applications to Quotient Geodesics
by: Bisson, Olivier, et al.
Published: (2024-11-01)