5 papers · 1 filter
GaINeR: Geometry-Aware Implicit Network Representation
Weronika Jakubowska, Mikołaj Zieliński, Rafał Tobiasz +4
Implicit Neural Representations (INRs) are widely used for modeling continuous 2D images, enabling high-fidelity reconstruction, super-resolution, and compression. Architectures su…
Affine-Equivariant Kernel Space Encoding for NeRF Editing
Mikołaj Zieliński, Krzysztof Byrski, Tomasz Szczepanik +2
Neural scene representations achieve high-fidelity rendering by encoding 3D scenes as continuous functions, but their latent spaces are typically implicit and globally entangled, m…
CEC-MMR: Cross-Entropy Clustering Approach to Multi-Modal Regression
Krzysztof Byrski, Jacek Tabor, Przemysław Spurek +1
In practical applications of regression analysis, it is not uncommon to encounter a multitude of values for each attribute. In such a situation, the univariate distribution, which…
REdiSplats: Ray Tracing for Editable Gaussian Splatting
Krzysztof Byrski, Grzegorz Wilczyński, Weronika Smolak-Dyżewska +4
Gaussian Splatting (GS) has become one of the most important neural rendering algorithms. GS represents 3D scenes using Gaussian components with trainable color and opacity. This r…
RaySplats: Ray Tracing based Gaussian Splatting
Krzysztof Byrski, Marcin Mazur, Jacek Tabor +4
3D Gaussian Splatting (3DGS) is a process that enables the direct creation of 3D objects from 2D images. This representation offers numerous advantages, including rapid training an…