Isometric Multi-Shape Matching

Abstract

Finding correspondences between shapes is a fundamental problem in computer vision and graphics, which is relevant for many applications, including 3D reconstruction, object tracking, and style transfer. The vast majority of correspondence methods aim to find a solution between pairs of shapes, even if multiple instances of the same class are available. While isometries are often studied in shape correspondence problems, they have not been considered explicitly in the multi-matching setting. This paper closes this gap by proposing a novel optimisation formulation for isometric multi-shape matching. We present a suitable optimisation algorithm for solving our formulation and provide a convergence and complexity analysis. Moreover, our algorithm obtains multi-matchings that are cycle-consistent without having to explicitly enforce cycle-consistency constraints. We demonstrate the superior performance of our method on various datasets and set the new state-of-the-art in isometric multi-shape matching.

Cite

Text

Gao et al. "Isometric Multi-Shape Matching." Conference on Computer Vision and Pattern Recognition, 2021. doi:10.1109/CVPR46437.2021.01396

Markdown

[Gao et al. "Isometric Multi-Shape Matching." Conference on Computer Vision and Pattern Recognition, 2021.](https://mlanthology.org/cvpr/2021/gao2021cvpr-isometric/) doi:10.1109/CVPR46437.2021.01396

BibTeX

@inproceedings{gao2021cvpr-isometric,
  title     = {{Isometric Multi-Shape Matching}},
  author    = {Gao, Maolin and Lahner, Zorah and Thunberg, Johan and Cremers, Daniel and Bernard, Florian},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2021},
  pages     = {14183-14193},
  doi       = {10.1109/CVPR46437.2021.01396},
  url       = {https://mlanthology.org/cvpr/2021/gao2021cvpr-isometric/}
}