PPC-MT: Parallel Point Cloud Completion with Mamba-Transformer Hybrid Architecture
Existing point cloud completion methods struggle to balance high-quality reconstruction with computational efficiency. To address this, we propose PPC-MT, a novel parallel framework for point cloud completion leveraging a hybrid Mamba-Transformer architecture. Our approach introduces an innovative parallel completion strategy guided by Principal Component Analysis (PCA), which imposes a geometrically meaningful structure on unordered point clouds, transforming them into ordered sets and decomposing them into multiple subsets. These subsets are reconstructed in parallel using a multi-head reconstructor. This structured parallel synthesis paradigm significantly enhances the uniformity of po...
| Authors | Jie Li, Shengwei Tian, Long Yu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 March 2026 |
| Last updated at source | 1 March 2026 |
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