2 citations · 5 across the 6 of their papers we have counts for
6 papers
CLEAR-NeRF: Collinearity and Local-region Enhanced Accurate 3D Reconstruction in Unbounded Scenes
Vladislav Polianskii, Elijs Dima, Isabel Salmerón Marazuela +3
Many real-world 3D reconstruction applications demand photorealism and metric accuracy across unbounded, complex scenes with challenging lighting and imperfect captures that curren…
Hyperbolic Delaunay Geometric Alignment
Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Vladislav Polianskii +4
Hyperbolic machine learning is an emerging field aimed at representing data with a hierarchical structure. However, there is a lack of tools for evaluation and analysis of the resu…
An Efficient and Continuous Voronoi Density Estimator
Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava +2
We introduce a non-parametric density estimator deemed Radial Voronoi Density Estimator (RVDE). RVDE is grounded in the geometry of Voronoi tessellations and as such benefits from…
Active Nearest Neighbor Regression Through Delaunay Refinement
Alexander Kravberg, Giovanni Luca Marchetti, Vladislav Polianskii +3
We introduce an algorithm for active function approximation based on nearest neighbor regression. Our Active Nearest Neighbor Regressor (ANNR) relies on the Voronoi-Delaunay framew…
Voronoi Density Estimator for High-Dimensional Data: Computation, Compactification and Convergence
Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg +3
The Voronoi Density Estimator (VDE) is an established density estimation technique that adapts to the local geometry of data. However, its applicability has been so far limited to…
Delaunay Component Analysis for Evaluation of Data Representations
Petra Poklukar, Vladislav Polianskii, Anastasia Varava +2
Advanced representation learning techniques require reliable and general evaluation methods. Recently, several algorithms based on the common idea of geometric and topological anal…