Consistent ZoomOut: Efficient Spectral Map Synchronization

Ruqi Huang, Jing Ren, Peter Wonka, Maks Ovsjanikov

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


In this paper, we propose a novel method, which we call Consistent ZoomOut, for efficiently refining correspondences among deformable 3D shape collections, while promoting the resulting map consistency. Our formulation is closely related to a recent unidirectional spectral refinement framework, but naturally integrates map consistency constraints into the refinement. Beyond that, we show further that our formulation can be adapted to recover the underlying isometry among near-isometric shape collections with a theoretical guarantee, which is absent in the other spectral map synchronization frameworks. We demonstrate that our method improves the accuracy compared to the competing methods when synchronizing correspondences in both near-isometric and heterogeneous shape collections, but also significantly outperforms the baselines in terms of map consistency.
Original languageEnglish (US)
Pages (from-to)265-278
Number of pages14
JournalComputer Graphics Forum
Issue number5
StatePublished - Aug 13 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): CRG-2017-3426
Acknowledgements: The authors thank the anonymous reviewers for their valuable comments. Parts of this work were supported by the KAUST OSR Award No. CRG-2017-3426 and the ERC Starting Grant No. 758800 (EXPROTEA).


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