Facial Depth and Normal Estimation using Single Dual-Pixel Camera

Understand

Many mobile manufacturers recently have adopted Dual-Pixel (DP) sensors in their flagship models for faster auto-focus and aesthetic image captures.

• Despite their advantages, research on their usage for 3D facial understanding has been limited due to the lack of datasets and algorithmic designs that exploit parallax in DP images.
• This is because the baseline of sub-aperture images is extremely narrow and parallax exists in the defocus blur region.
• In this paper, we introduce a DP-oriented Depth/Normal network that reconstructs the 3D facial geometry.