Spherical Tensor Calculus for Local Adaptive Filtering

By Marco Reisert, Hans Burkhardt. 2009

21 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Tess E. Smidt
2. Petar Velickovic
3. Regina Barzilay
4. Tommi S. Jaakkola
5. Risi Kondor
6. Erik J. Bekkers
7. David W. Romero
8. Max Welling

In Computer Vision and Pattern Recognition

1. Tess E. Smidt
2. Patrick F. Riley
3. Nathaniel Thomas
4. Petar Velickovic
5. Tommi S. Jaakkola
6. Regina Barzilay
7. Erik J. Bekkers
8. David W. Romero

Citations in the corpus

• Tensor Field Networks: Rotation- and Translation-Equivariant Neural Networks for 3D Point Clouds (2018, background): “However, the mathematics of rotation equivariance in 3D is much more complicated than in 2D because rotations in 3D do not commute; that is, for 3D rotation matrices A and B , AB (cid:54) = BA in general (see Reisert and Burkhardt [3] for more about the mathematics of tensors under 3D rotations).”