Search Results for author: Sławomir Tadeja

Found 5 papers, 5 papers with code

ImplicitDeepfake: Plausible Face-Swapping through Implicit Deepfake Generation using NeRF and Gaussian Splatting

1 code implementation9 Feb 2024 Georgii Stanishevskii, Jakub Steczkiewicz, Tomasz Szczepanik, Sławomir Tadeja, Jacek Tabor, Przemysław Spurek

NeRFs encode the object's shape and color in neural network weights using a handful of images with known camera positions to generate novel views.

Face Swapping

HyperPlanes: Hypernetwork Approach to Rapid NeRF Adaptation

1 code implementation2 Feb 2024 Paweł Batorski, Dawid Malarz, Marcin Przewięźlikowski, Marcin Mazur, Sławomir Tadeja, Przemysław Spurek

Neural radiance fields (NeRFs) are a widely accepted standard for synthesizing new 3D object views from a small number of base images.

Few-Shot Learning Object

GaMeS: Mesh-Based Adapting and Modification of Gaussian Splatting

1 code implementation2 Feb 2024 Joanna Waczyńska, Piotr Borycki, Sławomir Tadeja, Jacek Tabor, Przemysław Spurek

In comparison, 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, warranting fast training and swift, real-time rendering.

Gaussian Splatting with NeRF-based Color and Opacity

1 code implementation21 Dec 2023 Dawid Malarz, Weronika Smolak, Jacek Tabor, Sławomir Tadeja, Przemysław Spurek

To mitigate the caveats of both models, we propose a hybrid model Viewing Direction Gaussian Splatting (VDGS) that uses GS representation of the 3D object's shape and NeRF-based encoding of color and opacity.

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