Few-point Shape Completion Model for 3D Object Reconstruction
The author introduces the Few-point Shape Completion (FSC) model to address shape completion challenges with sparse point clouds, demonstrating superior performance over existing methods in both few-point and many-point scenarios.
3DMambaComplete: A Novel Point Cloud Completion Network Leveraging Structured State Space Model
3DMambaComplete, a novel point cloud completion network, effectively reconstructs complete and high-fidelity point clouds from incomplete and low-quality inputs by incorporating the Structured State Space Model framework.
Unsupervised Point Cloud Completion Using Unbalanced Optimal Transport Maps (UOT-UPC)
This paper introduces UOT-UPC, a novel unsupervised point cloud completion model that leverages unbalanced optimal transport maps to effectively handle class imbalance issues often present in unpaired datasets, achieving state-of-the-art results.
Enhancing Point Cloud Completion Networks with a Novel Consistency Loss Function
This research paper introduces a novel consistency loss function designed to enhance the performance of point cloud completion networks (PCCNs) by mitigating the one-to-many mapping problem inherent in reconstructing 3D objects from incomplete point cloud data.
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