Rethinking Amortized Neural Representations for High-Resolution Terrain Elevation Data
A controlled benchmark of amortized neural representations on high-resolution (1 m/pixel) terrain elevation data, and HUVR+SIREN — a hypernetwork with a smooth, analytically differentiable decoder that attains the best height and derivative fidelity with no extra per-tile storage.
Nov 3, 2026
ImplicitTerrainV2: Wavelet-Guided Spatially Adaptive Neural Terrain Representation
A wavelet-guided, spatially adaptive implicit neural representation for digital elevation models. A wavelet complexity field localizes high-frequency capacity to complex terrain, and post-training compression reaches 1.23 bpp — 66.25 dB PSNR on Swiss terrain tiles, +5.70 dB over prior work with 3.2x fewer parameters.
Nov 3, 2026
A Parallel Scale-Space Method for Critical Features Tracking on Triangulated Irregular Networks
A scale-space pipeline for terrain represented as Triangulated Irregular Networks (TINs): scale-aware seam-free sampling, an improved TIN smoothing operator, and a fully parallel GPU algorithm for tracking critical points across scales without global sorting.
May 8, 2026
Presentation of Scale Space for TINs @ ACM SIGSPATIAL2024
Oral presentation of our paper "Critical Features Tracking on Triangulated Irregular Networks by a Scale-Space Method" at the 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Oct 29, 2024
Critical Features Tracking on Triangulated Irregular Networks by a Scale-Space Method
Best Paper Runner-Up at ACM SIGSPATIAL 2024. A scale-space method that identifies and tracks topologically important terrain features directly on Triangulated Irregular Networks, handling irregular point distributions and boundaries that grid-based DEM methods cannot.
Sep 14, 2024
Presentation of ImplicitTerrain @ CVPR2024 INRV Workshop
We present our CVPR 2024 paper "ImplicitTerrain: a Continuous Surface Model for Terrain Data Analysis" at the 1st Workshop on Implicit Neural Representation for Vision
Jun 18, 2024
ImplicitTerrain: a Continuous Surface Model for Terrain Data Analysis
ImplicitTerrain models high-resolution digital terrain continuously and differentiably with an implicit neural representation, enabling accurate surface fitting and parallel topological feature extraction directly from the compact learned model.
Jun 18, 2024