Browsing by Author "Huang, Ruqi"

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    Consistent ZoomOut: Efficient Spectral Map Synchronization
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Huang, Ruqi; Ren, Jing; Wonka, Peter; Ovsjanikov, Maks; Jacobson, Alec and Huang, Qixing
    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.
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    Limit Shapes - A Tool for Understanding Shape Differences and Variability in 3D Model Collections
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Huang, Ruqi; Achlioptas, Panos; Guibas, Leonidas; Ovsjanikov, Maks; Bommes, David and Huang, Hui
    We propose a novel construction for extracting a central or limit shape in a shape collection, connected via a functional map network. Our approach is based on enriching the latent space induced by a functional map network with an additional natural metric structure. We call this shape-like dual object the limit shape and show that its construction avoids many of the biases introduced by selecting a fixed base shape or template. We also show that shape differences between real shapes and the limit shape can be computed and characterize the unique properties of each shape in a collection - leading to a compact and rich shape representation. We demonstrate the utility of this representation in a range of shape analysis tasks, including improving functional maps in difficult situations through the mediation of limit shapes, understanding and visualizing the variability within and across different shape classes, and several others. In this way, our analysis sheds light on the missing geometric structure in previously used latent functional spaces, demonstrates how these can be addressed and finally enables a compact and meaningful shape representation useful in a variety of practical applications.