76 citations · 257 across the 98 of their papers we have counts for
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Gaussian Splatting with NeRF-based Color and Opacity
Dawid Malarz, Weronika Smolak, Jacek Tabor +2
Neural Radiance Fields (NeRFs) have demonstrated the remarkable potential of neural networks to capture the intricacies of 3D objects. By encoding the shape and color information w…
MeVGAN: GAN-based Plugin Model for Video Generation with Applications in Colonoscopy
Łukasz Struski, Tomasz Urbańczyk, Krzysztof Bucki +4
Video generation is important, especially in medicine, as much data is given in this form. However, video generation of high-resolution data is a very demanding task for generative…
HyperMask: Adaptive Hypernetwork-based Masks for Continual Learning
Kamil Książek, Przemysław Spurek
Artificial neural networks suffer from catastrophic forgetting when they are sequentially trained on multiple tasks. Many continual learning (CL) strategies are trying to overcome…
MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation
Dominik Zimny, Artur Kasymov, Adam Kania +4
NeRF is a popular model that efficiently represents 3D objects from 2D images. However, vanilla NeRF has some important limitations. NeRF must be trained on each object separately.…
Gaussian model for closed curves
Krzysztof Byrski, Przemysław Spurek, Jacek Tabor
Gaussian Mixture Models (GMM) do not adapt well to curved and strongly nonlinear data. However, we can use Gaussians in the curvilinear coordinate systems to solve this problem. Mo…
NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering
Wojciech Zając, Joanna Waczyńska, Piotr Borycki +3
Traditional 3D face models are based on mesh representations with texture. One of the most important models is FLAME (Faces Learned with an Articulated Model and Expressions), whic…