Efficient Feature Fusion for Learning-Based Photometric Stereo

Yakun Ju, Kin Man Lam, Jun Xiao, Cong Zhang, Cuixin Yang, Junyu Dong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

10 Citations (Scopus)

Abstract

How to handle an arbitrary number for input images is a fundamental problem of learning-based photometric stereo methods. Existing approaches adopt max-pooling or observation map to fuse an arbitrary number of extracted features. However, these methods discard a large amount of the features from the input images, impacting the utilization and accuracy, or ignore the constraints from the intra-image spatial domain. In this paper, we explore how to efficiently fuse features from a variable number of input images. First, we propose a bilateral extraction module, which categorizes features into positive and negative, to maximally keep the useful feature in the fusion stage. Second, we adopt a top-k pooling to both the bilateral information, which selects the k maximum response value from all features. These two modules proposed are "plug-and-play"and can be used in different fusion tasks. We further propose a hierarchical photometric stereo network, namely HPS-Net, to handle bilateral extraction and top-k pooling for multiscale features. Experiments in the widely used benchmark illustrate the improvement of our proposed framework in the conventional max-pooling method and the proposed HPS-Net outperforms existing learning-based photometric stereo methods.

Original languageEnglish
Title of host publicationICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728163277
DOIs
Publication statusPublished - Jun 2023
Event48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023 - Rhodes Island, Greece
Duration: 4 Jun 202310 Jun 2023

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2023-June
ISSN (Print)1520-6149

Conference

Conference48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
Country/TerritoryGreece
CityRhodes Island
Period4/06/2310/06/23

Keywords

  • deep neural network
  • feature fusion
  • Photometric stereo

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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