SUPPLE: Extracting Hand Skeleton with Spherical Unwrapping Profiles


Zimeng Zhao, Ruting Rao and Yangang Wang


Embedding a unified skeleton into diverse hand meshes is a prominent task both for animation and pose estimation. Most existing methods extracted skeletons from humanoid characters under simple poses, for example T-pose or A-pose. Applying them directly to hand meshes may yield inaccurate or implausible results because hands have higher dexterity and similar endpoints. Furthermore, these methods did not attempt to extract skeleton directly from a scan model which may be not watertight and has much more vertices. Our key idea is to unwrap meshes with different topologies in the same image-based representation, named SUPPLE (Spherical UnwraPping ProfiLEs), and then train a convolutional encoder-decoder to extract skeleton under this representation. Experiments demonstrate that our framework produces reliable and accurate skeleton estimation results across a broad range of datasets, from raw scans to artist-designed models.

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  Important Dates

All deadlines are 23:59 Pacific Time (PT). No extensions will be granted.

Paper registration July 23 30, 2021
Paper submission July 30, 2021
Supplementary August 8, 2021
Tutorial submission August 15, 2021
Tutorial notification August 31, 2021
Rebuttal period September 16-22, 2021
Paper notification October 1, 2021
Camera ready October 15, 2021
Demo submission July 30 Nov 15, 2021
Demo notification Oct 1 Nov 19, 2021
Tutorial November 30, 2021
Main conference December 1-3, 2021