3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion

arXiv:2404.07106v1 Announce Type: new
Abstract: Point cloud completion aims to generate a complete and high-fidelity point cloud from an initially incomplete and low-quality input. A prevalent strategy involves leveraging Transformer-based models to encode global features and facilitate the reconstruction process. However, the adoption of pooling operations to obtain global feature representations often results in the loss of local details within the point cloud. Moreover, the attention mechanism inherent in Transformers introduces additional computational complexity, rendering it challenging to handle long …

abstract adoption arxiv cloud cs.cv cs.gr encode feature features fidelity generate global however low operations pooling process quality space state state space model strategy structured state space transformer transformer-based models type