Neural radiance-density field methods have become increasingly popular for the task of
novel-view rendering. Their recent extension to hash-based positional encoding ensures …

We present a novel deep neural network architecture for end-to-end scene flow estimation
that directly operates on large-scale 3D point clouds. Inspired by Bilateral Convolutional …

Many useful algorithms for processing images and geometry fall under the general
framework of high‐dimensional Gaussian filtering. This family of algorithms includes …

Deep convolutional neural networks (CNNs) have shown outstanding performance in the
task of semantically segmenting images. However, applying the same methods on 3D data …

Deep convolutional neural networks have shown outstanding performance in the task of
semantically segmenting images. Applying the same methods on 3D data still poses …

In this paper we study the connection between the zeros of the expected Euler characteristic
curve and the phenomenon which we refer to as homological percolation—the formation of …

We address the problem of autonomous exploration of unknown environments using a Micro
Aerial Vehicle (MAV) equipped with an active depth sensor. As such, the task consists in …

Classical methods to model topological properties of point clouds, such as the Vietoris–Rips
complex, suffer from the combinatorial explosion of complex sizes. We propose a novel …

A method of determining a hash code representing a portion of an image, is disclosed. A
Delaunay region (eg, 450) enclosing an image feature point (eg, 210) representing at least …

We study higher-dimensional homological analogues of bond percolation on a square
lattice and site percolation on a triangular lattice. By taking a quotient of certain infinite cell …