AI RESEARCH
3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion
arXiv CS.CV
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ArXi:2404.07106v2 Announce Type: replace 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