KBody: Towards general, robust, and aligned monocular whole-body estimation

KBody is a method for fitting a low-dimensional body model to an image. It follows a predict-and-optimize approach, relying on data-driven model estimates for the constraints that will be used to solve for the body's parameters. Acknowledging the importance of high quality correspondences, it l...

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Bibliographic Details
Published in:arXiv.org 2024-06
Main Authors: Zioulis, Nikolaos, O'Brien, James F
Format: Article
Language:English
Subjects:
Constraint modelling
Optimization
Parameter identification
Online Access:Get full text
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Summary:KBody is a method for fitting a low-dimensional body model to an image. It follows a predict-and-optimize approach, relying on data-driven model estimates for the constraints that will be used to solve for the body's parameters. Acknowledging the importance of high quality correspondences, it leverages ``virtual joints" to improve fitting performance, disentangles the optimization between the pose and shape parameters, and integrates asymmetric distance fields to strike a balance in terms of pose and shape capturing capacity, as well as pixel alignment. We also show that generative model inversion offers a strong appearance prior that can be used to complete partial human images and used as a building block for generalized and robust monocular body fitting. Project page: https://zokin.github.io/KBody.
ISSN:2331-8422
DOI:10.48550/arxiv.2304.11542