Loc-nerf: Monte carlo localization using neural radiance fields
We present Loc-NeRF, a real-time vision-based robot localization approach that combines
Monte Carlo localization and Neural Radiance Fields (NeRF). Our system uses a pre-trained …
Monte Carlo localization and Neural Radiance Fields (NeRF). Our system uses a pre-trained …
Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review
Despite its short history, the use of Riemannian geometry in brain-computer interface (BCI)
decoding is currently attracting increasing attention, due to accumulating documentation of …
decoding is currently attracting increasing attention, due to accumulating documentation of …
Rotation averaging
This paper is conceived as a tutorial on rotation averaging, summarizing the research that
has been carried out in this area; it discusses methods for single-view and multiple-view …
has been carried out in this area; it discusses methods for single-view and multiple-view …
[책][B] Passivity-based control and estimation in networked robotics
Passivity is an input–output property of dynamical systems. The concept generalizes
physical systems that cannot store more energy than the energy supplied from outside the …
physical systems that cannot store more energy than the energy supplied from outside the …
L1 rotation averaging using the Weiszfeld algorithm
We consider the problem of rotation averaging under the L 1 norm. This problem is related to
the classic Fermat-Weber problem for finding the geometric median of a set of points in IR n …
the classic Fermat-Weber problem for finding the geometric median of a set of points in IR n …
Manifoldnet: A deep neural network for manifold-valued data with applications
Geometric deep learning is a relatively nascent field that has attracted significant attention in
the past few years. This is partly due to the availability of data acquired from non-euclidean …
the past few years. This is partly due to the availability of data acquired from non-euclidean …
Computing the Karcher mean of symmetric positive definite matrices
DA Bini, B Iannazzo - Linear Algebra and its Applications, 2013 - Elsevier
Computing the Karcher mean of symmetric positive definite matrices Page 1 Linear Algebra and
its Applications 438 (2013) 1700–1710 Contents lists available at SciVerse ScienceDirect …
its Applications 438 (2013) 1700–1710 Contents lists available at SciVerse ScienceDirect …
Accelerated first-order methods for geodesically convex optimization on Riemannian manifolds
In this paper, we propose an accelerated first-order method for geodesically convex
optimization, which is the generalization of the standard Nesterov's accelerated method from …
optimization, which is the generalization of the standard Nesterov's accelerated method from …
On the convergence of gradient descent for finding the Riemannian center of mass
We study the problem of finding the global Riemannian center of mass of a set of data points
on a Riemannian manifold. Specifically, we investigate the convergence of constant step …
on a Riemannian manifold. Specifically, we investigate the convergence of constant step …
Organic priors in non-rigid structure from motion
This paper advocates the use of organic priors in classical non-rigid structure from motion
(NRS f M). By organic priors, we mean invaluable intermediate prior information intrinsic to …
(NRS f M). By organic priors, we mean invaluable intermediate prior information intrinsic to …