We present a simple and efficient method for refining maps or correspondences by iterative
upsampling in the spectral domain that can be implemented in a few lines of code. Our main
observation is that high quality maps can be obtained even if the input correspondences are
noisy or are encoded by a small number of coefficients in a spectral basis. We show how this
approach can be used in conjunction with existing initialization techniques across a range of
application scenarios, including symmetry detection, map refinement across complete …

Shape matching is a task that occurs in countless applications in computer graphics,
including shape interpolation [Kilian et al. 2007] and statistical shape analysis [Bogo et al.
2014], to name a few. An elegant approach to non-rigid shape correspondence is provided
by spectral techniques, which are broadly founded on the observation that near-isometric
shape matching can be formulated as an alignment problem in certain higher-dimensional
embedding