—We consider the problem of positioning a cloud of points in the Euclidean space Rd , from noisy measurements of a subset of pairwise distances. This task has applications in var...
We give a provably correct algorithm to reconstruct a kdimensional manifold embedded in d-dimensional Euclidean space. Input to our algorithm is a point sample coming from an unkn...
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time so...
Andrei Sharf, Dan A. Alcantara, Thomas Lewiner, Ch...
It has recently been shown that deformable 3D surfaces
could be recovered from single video streams. However, ex-
isting techniques either require a reference view in which
the ...
Aydin Varol, Mathieu Salzmann, Engin Tola, Pascal ...