3D face alignment approaches have strong advantages over 2D with respect to representational power and robustness to illumination and pose. Over the past few years, a number of research groups have made rapid advances in dense 3D alignment from 2D video and obtained impressive results. How these various methods compare is relatively unknown. Previous benchmarks addressed sparse 3D alignment and single image 3D reconstruction. No commonly accepted evaluation protocol exists for dense 3D face reconstruction from video with which to compare them. The 2nd 3D Face Alignment in the Wild from Videos (3DFAW-Video) Challenge extends the previous 3DFAW 2016 competition to the estimation of dense 3D facial structure from video. It presented a new large corpora of profile-to-profile face videos recorded under different imaging conditions and annotated with corresponding high-resolution 3D ground truth meshes. In this paper we outline the evaluation protocol, the data used, and the results. 3DFAW-Video is to be held in conjunction with the 2019 International Conference on Computer Vision, in Seoul, Korea.
R. K. Pillai et al., "The 2nd 3D Face Alignment In The Wild Challenge (3DFAW-video): Dense Reconstruction From Video," Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019, pp. 3082 - 3089, article no. 9022602, Institute of Electrical and Electronics Engineers, Oct 2019.
The definitive version is available at https://doi.org/10.1109/ICCVW.2019.00371
Keywords and Phrases
3D face dataset; 3D face modeling; 3D face reconstruction; 3D reconstruction challenge
International Standard Book Number (ISBN)
Article - Conference proceedings
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01 Oct 2019