AI RESEARCH
ImplicitTerrainV2: Wavelet-Guided Spatially Adaptive Neural Terrain Representation
arXiv CS.LG
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ArXi:2605.22556v1 Announce Type: new Digital elevation models (DEMs) underpin terrain analysis in Geographic Information Systems (GIS), but in their common raster form, they rely on interpolation for off-grid sampling and finite-difference operators for derivative-based analysis. Implicit neural representations (INRs) offer a continuous alternative, but prior terrain INRs lack explicit frequency control, neglect the gradient structure of terrain, and remain too large and costly to train for practical deployment.