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arXiv · 2304.11542

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

Nikolaos Zioulis·James F. O'Brien
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Abstract

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.

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Nikolaos Zioulis, James F. O'Brien. 2023-04-23. KBody: Towards general, robust, and aligned monocular whole-body estimation. https://doi.org/10.1109/cvprw59228.2023.00661

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