Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos

Yikai Wang; Yinpeng Dong; Fuchun Sun; Xiao Yang

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arXiv · 2308.10089

Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos

Yikai Wang·Yinpeng Dong·Fuchun Sun·Xiao Yang

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Abstract

This work focuses on the 3D reconstruction of non-rigid objects based on monocular RGB video sequences. Concretely, we aim at building high-fidelity models for generic object categories and casually captured scenes. To this end, we do not assume known root poses of objects, and do not utilize category-specific templates or dense pose priors. The key idea of our method, Root Pose Decomposition (RPD), is to maintain a per-frame root pose transformation, meanwhile building a dense field with local transformations to rectify the root pose. The optimization of local transformations is performed by point registration to the canonical space. We also adapt RPD to multi-object scenarios with object occlusions and individual differences. As a result, RPD allows non-rigid 3D reconstruction for complicated scenarios containing objects with large deformations, complex motion patterns, occlusions, and scale diversities of different individuals. Such a pipeline potentially scales to diverse sets of objects in the wild. We experimentally show that RPD surpasses state-of-the-art methods on the challenging DAVIS, OVIS, and AMA datasets.

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Yikai Wang, Yinpeng Dong, Fuchun Sun, Xiao Yang. 2023-08-19. Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos. https://arxiv.org/abs/2308.10089

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