Abstract: Neural implicit functions including signed distance functions (SDFs) and unsigned distance functions (UDFs) have shown powerful ability in fitting the shape geometry. However, inferring ...
Localization of a robotic system within a previously mapped environment is important for reducing estimation drift and for reusing previously built maps. Existing techniques for geometry-based ...
This repository contains the code to reproduce the results from the paper. Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces. You can find ...
Our preprocessed datasets are provided in This link. For DTU dataset, download the pair file for the warp loss. Please organize all files as follows: data ├── deepfashion_rendering_fov60 │ ├── 30 │ │ ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results