Cloud Sphere: A 3D Shape Representation via Progressive Deformation

• URL: http://arxiv.org/abs/2112.11133v1
• Date: Tue, 21 Dec 2021 12:10:23 GMT
• Title: Cloud Sphere: A 3D Shape Representation via Progressive Deformation
• Authors: Zongji Wang, Yunfei Liu, Feng Lu
• Abstract summary: This paper is dedicated to discovering distinctive information from the shape formation process. A Progressive Deformation-based Auto-Encoder is proposed to learn the stage-aware description. Experimental results show that the proposed PDAE has the ability to reconstruct 3D shapes with high fidelity.
• Score: 21.216503294296317
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In the area of 3D shape analysis, the geometric properties of a shape have long been studied. Instead of directly extracting representative features using expert-designed descriptors or end-to-end deep neural networks, this paper is dedicated to discovering distinctive information from the shape formation process. Concretely, a spherical point cloud served as the template is progressively deformed to fit the target shape in a coarse-to-fine manner. During the shape formation process, several checkpoints are inserted to facilitate recording and investigating the intermediate stages. For each stage, the offset field is evaluated as a stage-aware description. The summation of the offsets throughout the shape formation process can completely define the target shape in terms of geometry. In this perspective, one can derive the point-wise shape correspondence from the template inexpensively, which benefits various graphic applications. In this paper, the Progressive Deformation-based Auto-Encoder (PDAE) is proposed to learn the stage-aware description through a coarse-to-fine shape fitting task. Experimental results show that the proposed PDAE has the ability to reconstruct 3D shapes with high fidelity, and consistent topology is preserved in the multi-stage deformation process. Additional applications based on the stage-aware description are performed, demonstrating its universality.

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