Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces.
Martin RynerJan KronqvistJohan KarlssonPublished in: CoRR (2023)
Keyphrases
- euclidean space
- point cloud
- low dimensional
- high dimensional
- higher dimensional
- structure from motion
- pairwise distances
- wide class
- dimensionality reduction
- point cloud data
- point sets
- data points
- metric space
- high dimensional data
- riemannian manifolds
- embedding space
- laser scanner
- vector space
- manifold learning
- geodesic distance
- euclidean distance
- shape analysis
- feature space
- principal component analysis
- dimension reduction
- input space
- image sequences
- viewpoint
- laplace beltrami
- three dimensional
- computer vision