Reducing the Gap Between Spatial and Space-Filling Curve Neighbors in 3D Point Cloud Segmentation

cs.CV

Submitted: 2026-10-14

Updated: 2026-10-14

Comments: Accepted by ECCV2026 Workshop "3rd Workshop on Scalable 3D Scene Generation and Geometric Scene Understanding"

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• Point-MoE: Large-Scale Multi-Dataset Training with Mixture-of-Experts for 3D Semantic Segmentation
• Vehicle Detection from 3D Lidar Using Fully Convolutional Network
• SGDR: Stochastic Gradient Descent with Warm Restarts
• Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
• PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
• DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation

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