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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…
GASP: Gaussian Splatting for Physic-Based Simulations
Piotr Borycki, Weronika Smolak, Joanna WaczyÅska +3
Physics simulation is paramount for modeling and utilizing 3D scenes in various real-world applications. However, integrating with state-of-the-art 3D scene rendering techniques su…
REdiSplats: Ray Tracing for Editable Gaussian Splatting
Krzysztof Byrski, Grzegorz WilczyÅski, 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…
D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup
Joanna WaczyÅska, Piotr Borycki, Joanna Kaleta +2
Over the past years, we have observed an abundance of approaches for modeling dynamic 3D scenes using Gaussian Splatting (GS). Such solutions use GS to represent the scene's struct…
Deepfake for the Good: Generating Avatars through Face-Swapping with Implicit Deepfake Generation
Georgii Stanishevskii, Jakub Steczkiewicz, Tomasz Szczepanik +3
Numerous emerging deep-learning techniques have had a substantial impact on computer graphics. Among the most promising breakthroughs are the rise of Neural Radiance Fields (NeRFs)…
GaMeS: Mesh-Based Adapting and Modification of Gaussian Splatting
Joanna WaczyÅska, Piotr Borycki, SÅawomir Tadeja +2
Gaussian Splatting (GS) is a novel, state-of-the-art technique for rendering points in a 3D scene by approximating their contribution to image pixels through Gaussian distributions…