From the 1 of 65 linked papers with an AI index.
1 citations · 2 across the 32 of their papers we have counts for
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COGENT: Counterfactual Gaussian Explanations for Volumetric Medical Images
Dorian Rząsa, Bartosz Zabdyr, Krzysztof Piekarz +7
Explainability is essential for deploying deep learning models in high-stakes medical applications. Existing explainability methods for volumetric imaging predominantly operate in…
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…
TOM-GS: Editable Video Representation via Temporal Opacity Modulation of Static 3D Gaussians
Marek Lisowski, Åukasz SmoliÅski, Kornel Howil +3
While Implicit Neural Representations (INRs) and dynamic 3D Gaussian Splatting (3DGS) achieve impressive results in video processing, they often fall short of producing representat…
OmniStyle-INR: Universal and Multimodal Style Transfer for INRs
RafaÅ Kajca, MichaÅ MizioÅek, Kornel Howil +2
Style transfer remains a fundamental and highly important task across various data modalities, enabling creative manipulation conditioned by both reference images and textual descr…
AnyStyle: Single-Pass Multimodal Stylization for 3D Gaussian Splatting
Joanna Kaleta, Bartosz Åwirta, Kacper Kania +3
AnyStyle is a feed‑forward framework that adds multimodal (text or image) style control to pose‑free 3D Gaussian Splatting reconstruction, enabling zero‑shot stylization while keep…
MiraGe: Editable 2D Images using Gaussian Splatting
Joanna WaczyÅska, Tomasz Szczepanik, Piotr Borycki +3
Implicit Neural Representations (INRs) approximate discrete data through continuous functions and are commonly used for encoding 2D images. Traditional image-based INRs employ neur…