7 citations · 9 across the 8 of their papers we have counts for
4 papers · 1 filter
Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D Features
Thomas Wimmer, Peter Wonka, Maks Ovsjanikov
With the immense growth of dataset sizes and computing resources in recent years, so-called foundation models have become popular in NLP and vision tasks. In this work, we propose…
Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training
Miriam Anschütz, Joshua Oehms, Thomas Wimmer +2
Automatic text simplification systems help to reduce textual information barriers on the internet. However, for languages other than English, only few parallel data to train these…
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution
Hoai Nam Dang, Vladimir Golkov, Thomas Wimmer +3
Current MRI super-resolution (SR) methods only use existing contrasts acquired from typical clinical sequences as input for the neural network (NN). In turbo spin echo sequences (T…
Scale-Equivariant Deep Learning for 3D Data
Thomas Wimmer, Vladimir Golkov, Hoai Nam Dang +3
The ability of convolutional neural networks (CNNs) to recognize objects regardless of their position in the image is due to the translation-equivariance of the convolutional opera…