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3DCMM: 3D Comprehensive Morphable Models With UV-UNet for Accurate Head Creation

  • Jie Zhang
  • , Kangneng Zhou
  • , Yan Luximon
  • , Tong Yee Lee
  • , Ping Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In recent studies of 3D shape modelling and reconstruction, the focus has primarily been on the 3D face region. However, accurately creating the entire 3D head opens up a wide range of applications, including headwear design, cranial diagnosis, and avatar design. Therefore, we present our newly developed method of constructing 3D comprehensive morphable models (3DCMM) specifically tailored for human heads, along with a novel 3DCMM-based stepwise pipeline for creating accurate full 3D heads. Within our 3DCMM framework, we constructed a powerful 3D morphable face model with UV-UNet to generate the 3D face and predict the 3D scalp, resulting in a complete representation of the head. Additionally, our 3DCMM-based self-learning approach incorporates novel facial boundary-aware and structure-aware losses for highly accurate overall reconstructions of the entire facial region. Experimental evaluations demonstrate that our 3DCMM exhibits superior face representation power and achieves higher head prediction accuracy than existing models. Consequently, our 3DCMM-based 3D head creation method from a single image demonstrates outstanding performance capability on both face and head benchmarks.

Original languageEnglish
Pages (from-to)1887-1900
Number of pages14
JournalIEEE Transactions on Multimedia
Volume27
DOIs
Publication statusPublished - 23 Dec 2024

Keywords

  • 3D face reconstruction
  • 3D head creation
  • 3D morphable model
  • 3D scalp completion

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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