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Large Scale 3D Morphable Models.

James Booth¹, Anastasios Roussos^1,2, Allan Ponniah³

¹1Imperial College London, London, UK.

International Journal of Computer Vision

|January 28, 2020

Summary

We introduce the Large Scale Facial Model (LSFM), the largest 3D Morphable Model (3DMM) to date, built using an automated pipeline. LSFM offers superior performance in facial analysis tasks and is publicly available for research.

Keywords:

3D morphable models Demographic-specific models Dense correspondence

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Area of Science:

Computer Vision
3D Computer Graphics
Biometrics

Background:

3D Morphable Models (3DMMs) are crucial for facial analysis.
Existing 3DMMs lack scale and diversity, limiting their applicability.
Automated construction of large-scale 3DMMs is challenging.

Purpose of the Study:

To introduce the Large Scale Facial Model (LSFM), the largest 3DMM constructed to date.
To develop a novel, automated pipeline for robust 3DMM construction.
To enable tailored 3DMMs for specific demographic groups and improve facial analysis.

Main Methods:

Developed a fully automated and robust pipeline for 3DMM construction.
Utilized state-of-the-art dense correspondence techniques.
Trained the model on 9663 distinct facial identities with rich demographic data.

Main Results:

Constructed the Large Scale Facial Model (LSFM), the largest 3DMM to date.
Achieved state-of-the-art results in age classification and noisy data reconstruction.
Demonstrated superior performance over existing 3DMMs through extensive evaluations.

Conclusions:

The proposed automated pipeline enables the creation of unprecedentedly large and diverse 3DMMs.
LSFM and its tailored variants significantly advance facial analysis capabilities.
The LSFM code and models are released to the research community.