Search Results for author:
Found 6 papers, 1 papers with code
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis
In experimental evaluations we demonstrate that the proposed FLBO is a valuable alternative to the traditional Riemannian-based LBO and ALBOs for spatial filtering and shape correspondence estimation.
On Partial Shape Correspondence and Functional Maps
Our study of functional maps led us to a novel method that establishes direct correspondence between partial and full shapes through feature matching bypassing the need for functional map intermediate spaces.
A model is worth tens of thousands of examples
Traditional signal processing methods relying on mathematical data generation models have been cast aside in favour of deep neural networks, which require vast amounts of data.
From Compass and Ruler to Convolution and Nonlinearity: On the Surprising Difficulty of Understanding a Simple CNN Solving a Simple Geometric Estimation Task
Neural networks are omnipresent, but remain poorly understood.
Seeing Things in Random-Dot Videos
Humans possess an intricate and powerful visual system in order to perceive and understand the environing world.
Probabilistic Gathering Of Agents With Simple Sensors
Two types of motion are considered: when no peers are detected behind them, either the agents perform unit jumps forward, or they start to move with unit speed while continuously sensing their back half-plane, and stop whenever another agent appears there.
Multiagent Systems
