Physical Sciences and Mathematics Commons^™

The 2nd 3d Face Alignment In The Wild Challenge (3dfaw-Video): Dense Reconstruction From Video, Rohith Krishnan Pillai, Laszlo Attila Jeni, Huiyuan Yang, Zheng Zhang, Lijun Yin, Jeffrey F. Cohn

Computer Science Faculty Research & Creative Works

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 …