1 code implementation • 11 Mar 2024 • Bram Vanherle, Nick Michiels, Frank Van Reeth
This is because they widen the training data distribution, thus encouraging the model to generalize better to other domains.
no code implementations • 16 Feb 2024 • Bram Vanherle, Vittorio Pippi, Silvia Cascianelli, Nick Michiels, Frank Van Reeth, Rita Cucchiara
Styled Handwritten Text Generation (HTG) has received significant attention in recent years, propelled by the success of learning-based solutions employing GANs, Transformers, and, preliminarily, Diffusion Models.
1 code implementation • 29 Nov 2022 • Bram Vanherle, Steven Moonen, Frank Van Reeth, Nick Michiels
The downside of this technique is that the so-called domain gap between the real target images and synthetic training data leads to a decrease in performance.
1 code implementation • 25 Nov 2022 • Steven Moonen, Bram Vanherle, Joris de Hoog, Taoufik Bourgana, Abdellatif Bey-Temsamani, Nick Michiels
The use of computer vision for product and assembly quality control is becoming ubiquitous in the manufacturing industry.
no code implementations • 21 Oct 2022 • Bram Vanherle, Jeroen Put, Nick Michiels, Frank Van Reeth
To avoid the need for an exact textured 3D model of the tool in question, it is shown that the model will generalize to an unseen tool when trained on a set of different 3D models of the same type of tool.
no code implementations • 10 Aug 2022 • Bram Vanherle, Tim Vervoort, Nick Michiels, Philippe Bekaert
Using a user study it is shown, for a number of different scenarios, that the proposed automated director is able to capture an event with aesthetically pleasing video compositions and human-like shot switching behavior.
1 code implementation • 8 Aug 2022 • Peter De Roovere, Steven Moonen, Nick Michiels, Francis wyffels
The close correspondence between synthetic and real-world data, and controlled variations, will facilitate sim-to-real research.