Diverse Part Synthesis for 3D Shape Creation

arXiv:2401.09384v2 Announce Type: replace-cross
Abstract: Methods that use neural networks for synthesizing 3D shapes in the form of a part-based representation have been introduced over the last few years. These methods represent shapes as a graph or hierarchy of parts and enable a variety of applications such as shape sampling and reconstruction. However, current methods do not allow easily regenerating individual shape parts according to user preferences. In this paper, we investigate techniques that allow the user to generate multiple, …

abstract applications arxiv cs.cv cs.gr cs.lg diverse form graph however networks neural networks part replace representation sampling shape synthesis type