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Found 5 papers, 2 papers with code
Robust Fine-tuning for Pre-trained 3D Point Cloud Models
We apply this robust fine-tuning method to mainstream 3D point cloud pre-trained models and evaluate the quality of model parameters and the degradation of downstream task performance.
Point Cloud Part Editing: Segmentation, Generation, Assembly, and Selection
Based on this process, we introduce SGAS, a model for part editing that employs two strategies: feature disentanglement and constraint.
SRPCN: Structure Retrieval based Point Completion Network
Besides, the missing patterns are diverse in reality, but existing methods can only handle fixed ones, which means a poor generalization ability.
Generate Point Clouds with Multiscale Details from Graph-Represented Structures
As details are missing in most representations of structures, the lack of controllability to details is one of the major weaknesses in structure-based controllable point cloud generation.
Attention-based Transformation from Latent Features to Point Clouds
The points generated by AXform do not have the strong 2-manifold constraint, which improves the generation of non-smooth surfaces.
