6 papers · 1 filter
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…
A Comparative Evaluation of Geometric Accuracy in NeRF and Gaussian Splatting
Mikolaj Zielinski, Eryk Vykysaly, Bartlomiej Biesiada +3
Recent advances in neural rendering have introduced numerous 3D scene representations. Although standard computer vision metrics evaluate the visual quality of generated images, th…
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…
Pointy - A Lightweight Transformer for Point Cloud Foundation Models
Konrad Szafer, Marek Kraft, Dominik Belter
Foundation models for point cloud data have recently grown in capability, often leveraging extensive representation learning from language or vision. In this work, we take a more c…
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…