KBody: Towards general, robust, and aligned monocular whole-body estimation
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866909224211054592 |
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| author | Zioulis, Nikolaos O'Brien, James F. |
| author_facet | Zioulis, Nikolaos O'Brien, James F. |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2304_11542 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | KBody: Towards general, robust, and aligned monocular whole-body estimation Zioulis, Nikolaos O'Brien, James F. Computer Vision and Pattern Recognition 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. |
| title | KBody: Towards general, robust, and aligned monocular whole-body estimation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2304.11542 |