9 papers
Floating Radiance Networks
Krzysztof Byrski, Rafał Tobiasz, Grzegorz Wilczyński +5
Recent advances in neural scene representations enable photorealistic novel-view synthesis, yet most methods remain tightly coupled to a single rendering paradigm, limiting their v…
IRIS: Intersection-aware Ray-based Implicit Editable Scenes
Grzegorz Wilczyński, Mikołaj Zieliński, Krzysztof Byrski +3
Neural Radiance Fields achieve high-fidelity scene representation but suffer from costly training and rendering, while 3D Gaussian splatting offers real-time performance with stron…
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…
Gaussian model for closed curves
Krzysztof Byrski, Przemysław Spurek, Jacek Tabor
Gaussian Mixture Models (GMM) do not adapt well to curved and strongly nonlinear data. However, we can use Gaussians in the curvilinear coordinate systems to solve this problem. Mo…
Active Function Cross-Entropy Clustering
P. Spurek, J. Tabor, P. Markowicz
Gaussian Mixture Models (GMM) have found many applications in density estimation and data clustering. However, the model does not adapt well to curved and strongly nonlinear data.…