FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction

Haoran Bai, Di Kang, Haoxian Zhang, Jinshan Pan, Linchao Bao

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

Abstract

We present a large-scale facial UV-texture dataset that contains over 50,000 high-quality texture UV-maps with even illuminations, neutral expressions, and cleaned facial regions, which are desired characteristics for rendering realistic 3D face models under different lighting conditions. The dataset is derived from a large-scale face image dataset namely FFHQ, with the help of our fully automatic and robust UV-texture production pipeline. Our pipeline utilizes the recent advances in StyleGAN-based facial image editing approaches to generate multi-view normalized face images from single-image inputs. An elaborated UV-texture extraction, correction, and completion procedure is then applied to produce high-quality UV-maps from the normalized face images. Compared with existing UV-texture datasets, our dataset has more diverse and higher-quality texture maps. We further train a GAN-based texture decoder as the nonlinear texture basis for parametric fitting based 3D face reconstruction. Experiments show that our method improves the reconstruction accuracy over state-of-the-art approaches, and more importantly, produces high-quality texture maps that are ready for realistic renderings. The dataset, code, and pre-trained texture decoder are publicly available at https://github.com/csbhr/FFHQ-UV.
Original languageEnglish
Title of host publication2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
PublisherIEEE
Pages362-371
Number of pages10
ISBN (Electronic)9798350301298
ISBN (Print)9798350301304 (PoD)
DOIs
Publication statusPublished - 22 Aug 2023
Event2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) - Vancouver, BC, Canada
Duration: 17 Jun 202324 Jun 2023

Publication series

NameProceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE
ISSN (Print)1063-6919
ISSN (Electronic)2575-7075

Conference

Conference2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Period17/06/2324/06/23

Keywords

  • Solid modeling
  • Three-dimensional displays
  • Face recognition
  • Pipelines
  • Fitting
  • Lighting
  • Production

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