1 code implementation • 11 Feb 2021 • Przemysław Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Sławomir Tadeja, Łukasz Struski, Jacek Tabor, Tomasz Trzciński
In this work, we reformulate the problem of point cloud completion into an object hallucination task.
1 code implementation • 4 Oct 2022 • Sajad Darabi, Piotr Bigaj, Dawid Majchrowski, Artur Kasymov, Pawel Morkisz, Alex Fit-Florea
Recently there has been increasing interest in developing and deploying deep graph learning algorithms for many tasks, such as fraud detection and recommender systems.
1 code implementation • 27 Jan 2023 • Adam Kania, Artur Kasymov, Maciej Zięba, Przemysław Spurek
Our architecture produces 2D images, but we use 3D-aware NeRF representation, which forces the model to produce correct 3D objects.
1 code implementation • 8 Feb 2023 • Mohammadreza Banaei, Klaudia Bałazy, Artur Kasymov, Rémi Lebret, Jacek Tabor, Karl Aberer
Recent transformer language models achieve outstanding results in many natural language processing (NLP) tasks.
1 code implementation • 17 May 2023 • Dominik Zimny, Artur Kasymov, Adam Kania, Jacek Tabor, Maciej Zięba, Przemysław Spurek
Furthermore, we can train MultiPlaneNeRF on a large data set and force our implicit decoder to generalize across many objects.