7 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…
NEO: NeRF It Once, Edit It Many Times for Continuous Object Manipulation
MikoÅaj ZieliÅski, David Hall, Dominik Belter +1
In this paper, we present NEO, a unified framework providing language-guided NeRF editing for robotic manipulation. Our paper introduces (i) a language-guided object removal that c…
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…
GaINeR: Geometry-Aware Implicit Network Representation
Weronika Jakubowska, MikoÅaj ZieliÅski, RafaÅ Tobiasz +4
Implicit Neural Representations (INRs) are widely used for modeling continuous 2D images, enabling high-fidelity reconstruction, super-resolution, and compression. Architectures su…
IRIS: Intersection-aware Ray-based Implicit Editable Scenes
Grzegorz WilczyÅski, MikoÅaj ZieliÅski, 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…