Surface Hof: Surface Reconstruction from A Single Image Using Higher Order Function Networks

Ziyun Wang, Volkan Isler, Daniel D. Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We address the problem of reconstructing a high-resolution surface representing an object from a single image. We present Surface HOF, which takes an image of an object as input and generates a mapping function for surface generation. The mapping function takes samples from a canonical domain and maps each sample to a local tangent plane on the 3D reconstruction of the object. By efficiently learning a continuous mapping function, the surface can be generated at arbitrary resolution in contrast to other methods which generate fixed resolution outputs. Experiments show that Surface HOF is more accurate and uses more efficient representations than other state of the art methods for surface reconstruction. Surface HOF is also easier to train: it requires minimal input pre-processing and output post-processing and generates surface representations that are more parameter efficient. Its accuracy and convenience make Surface HOF an appealing method for single image reconstruction.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings
PublisherIEEE Computer Society
Pages2666-2670
Number of pages5
ISBN (Electronic)9781728163956
DOIs
StatePublished - Oct 2020
Event2020 IEEE International Conference on Image Processing, ICIP 2020 - Virtual, Abu Dhabi, United Arab Emirates
Duration: Sep 25 2020Sep 28 2020

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2020-October
ISSN (Print)1522-4880

Conference

Conference2020 IEEE International Conference on Image Processing, ICIP 2020
CountryUnited Arab Emirates
CityVirtual, Abu Dhabi
Period9/25/209/28/20

Keywords

  • Computer Graphics
  • Computer Vision
  • Deep Learning
  • Monocular 3D Reconstruction
  • Surface reconstruction

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