SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural Representations. (arXiv:2210.02299v1 [cs.CV])

Accurate mapping of large-scale environments is an essential building block
of most outdoor autonomous systems. Challenges of traditional mapping methods
include the balance between memory consumption and mapping accuracy. This paper
addresses the problems of achieving large-scale 3D reconstructions with
implicit representations using 3D LiDAR measurements. We learn and store
implicit features through an octree-based hierarchical structure, which is
sparse and extensible. The features can be turned into signed distance values
through a shallow neural network. We leverage binary cross …

3d mapping arxiv hierarchical mapping scale