Zobrazeno 1 - 10
of 189
pro vyhledávání: '"Mazur, Marcin"'
Autor:
Borycki, Piotr, Smolak, Weronika, Waczyńska, Joanna, Mazur, Marcin, Tadeja, Sławomir, Spurek, Przemysław
Physics simulation is paramount for modeling and utilization of 3D scenes in various real-world applications. However, its integration with state-of-the-art 3D scene rendering techniques such as Gaussian Splatting (GS) remains challenging. Existing m
Externí odkaz:
http://arxiv.org/abs/2409.05819
Autor:
Trędowicz, Magdalena, Struski, Łukasz, Mazur, Marcin, Janusz, Szymon, Lewicki, Arkadiusz, Tabor, Jacek
Video processing is generally divided into two main categories: processing of the entire video, which typically yields optimal classification outcomes, and real-time processing, where the objective is to make a decision as promptly as possible. The l
Externí odkaz:
http://arxiv.org/abs/2406.11443
One of the key advantages of 3D rendering is its ability to simulate intricate scenes accurately. One of the most widely used methods for this purpose is Gaussian Splatting, a novel approach that is known for its rapid training and inference capabili
Externí odkaz:
http://arxiv.org/abs/2405.18163
Autor:
Batorski, Paweł, Malarz, Dawid, Przewięźlikowski, Marcin, Mazur, Marcin, Tadeja, Sławomir, Spurek, Przemysław
Neural radiance fields (NeRFs) are a widely accepted standard for synthesizing new 3D object views from a small number of base images. However, NeRFs have limited generalization properties, which means that we need to use significant computational re
Externí odkaz:
http://arxiv.org/abs/2402.01524
Autor:
Kania, Adam, Kasymov, Artur, Kościukiewicz, Jakub, Górak, Artur, Mazur, Marcin, Zięba, Maciej, Spurek, Przemysław
The recent surge in popularity of deep generative models for 3D objects has highlighted the need for more efficient training methods, particularly given the difficulties associated with training with conventional 3D representations, such as voxels or
Externí odkaz:
http://arxiv.org/abs/2301.11631
Many crucial problems in deep learning and statistics are caused by a variational gap, i.e., a difference between evidence and evidence lower bound (ELBO). As a consequence, in the classical VAE model, we obtain only the lower bound on the log-likeli
Externí odkaz:
http://arxiv.org/abs/2206.09453
We propose an effective regularization strategy (CW-TaLaR) for solving continual learning problems. It uses a penalizing term expressed by the Cramer-Wold distance between two probability distributions defined on a target layer of an underlying neura
Externí odkaz:
http://arxiv.org/abs/2111.07928
Recently introduced implicit field representations offer an effective way of generating 3D object shapes. They leverage implicit decoder trained to take a 3D point coordinate concatenated with a shape encoding and to output a value which indicates wh
Externí odkaz:
http://arxiv.org/abs/2110.05770
Autor:
Spurek, Przemysław, Winczowski, Sebastian, Zięba, Maciej, Trzciński, Tomasz, Kania, Kacper, Mazur, Marcin
Recently proposed 3D object reconstruction methods represent a mesh with an atlas - a set of planar patches approximating the surface. However, their application in a real-world scenario is limited since the surfaces of reconstructed objects contain
Externí odkaz:
http://arxiv.org/abs/2102.05984
Autor:
Spurek, Przemysław, Kasymov, Artur, Mazur, Marcin, Janik, Diana, Tadeja, Sławomir, Struski, Łukasz, Tabor, Jacek, Trzciński, Tomasz
Scanning real-life scenes with modern registration devices typically give incomplete point cloud representations, mostly due to the limitations of the scanning process and 3D occlusions. Therefore, completing such partial representations remains a fu
Externí odkaz:
http://arxiv.org/abs/2102.05973