ThingiPano: A Large-Scale Dataset of 3D Printing Metadata, Images, and Panoramic Renderings for Exploring Design Reuse

The emergence of consumer-grade 3D printing has democratized innovation through online design-sharing platforms like Thingiverse. We introduce a novel multimodal dataset called "ThingiPano", a large-scale collection containing multi-view 2D panoramic representations of over a million 3D files (n=1,052,017) with associated user-uploaded images (n=1,816,288), design metadata (n=1,017,687), and user meta-data (n=283,873) from Thingiverse. In this paper, we exhibit how ThingiPano's metadata can facilitate greater understanding of how 3D printing designs are fabricated, by who, and for what purpose. We demonstrate how this novel multimodal dataset is sufficient for self-supervised machine learning methodologies. Such methodologies have the potential to facilitate broader reuse of 3D printable designs, through improved multimodal classification and retrieval in various applications from online file-sharing platforms to design-tools.