We argue that extracting explicit surfaces from neural unsigned distance fields benefits from multi-pass approaches, as they can refine surface predictions over time! Compared to perfect fields, neural ones have noisy spots which are missed by single-pass meshing techniques.

If you are at @neuripsconf.bsky.social in San Diego come say hi! I'll be presenting my latest paper "High Resolution UDF Meshing via Iterative Networks" at the poster session on Friday from 11am to 2pm🧑‍🔬

ilceltico.github.io/hrudf/

#NeurIPS2025 #NeurIPS #Research #AI #ComputerVision