Video to Fully Automatic 3D Hair Model

TL;DR

This paper introduces an automatic system that reconstructs detailed 3D hair models from casual videos, including selfies, without manual input, leveraging 3D hair strand estimation for improved accuracy.

Contribution

It presents a fully automatic 3D hair reconstruction method from videos that does not require specific views or manual segmentation, utilizing 3D hair strand estimation.

Findings

Achieved high-quality 3D hair reconstructions from diverse videos

Validated system effectiveness through qualitative and quantitative studies

Demonstrated applicability on celebrity and selfie videos

Abstract

Imagine taking a selfie video with your mobile phone and getting as output a 3D model of your head (face and 3D hair strands) that can be later used in VR, AR, and any other domain. State of the art hair reconstruction methods allow either a single photo (thus compromising 3D quality) or multiple views, but they require manual user interaction (manual hair segmentation and capture of fixed camera views that span full 360 degree). In this paper, we describe a system that can completely automatically create a reconstruction from any video (even a selfie video), and we don't require specific views, since taking your -90 degree, 90 degree, and full back views is not feasible in a selfie capture. In the core of our system, in addition to the automatization components, hair strands are estimated and deformed in 3D (rather than 2D as in state of the art) thus enabling superior results. We provide qualitative, quantitative, and Mechanical Turk human studies that support the proposed system, and show results on a diverse variety of videos (8 different celebrity videos, 9 selfie mobile videos, spanning age, gender, hair length, type, and styling).