1 citations · 2 across the 7 of their papers we have counts for
16 papers
Wavelength-aware 2D Convolutions for Hyperspectral Imaging
Leon Amadeus Varga, Martin Messmer, Nuri Benbarka +1
Deep Learning could drastically boost the classification accuracy for Hyperspectral Imaging (HSI). Still, the training on the mostly small hyperspectral data sets is not trivial. T…
Seeing Implicit Neural Representations as Fourier Series
Nuri Benbarka, Timon Höfer, Hamd ul-moqeet Riaz +1
Implicit Neural Representations (INR) use multilayer perceptrons to represent high-frequency functions in low-dimensional problem domains. Recently these representations achieved s…
Separable Convolutions for Optimizing 3D Stereo Networks
Rafia Rahim, Faranak Shamsafar, Andreas Zell
Deep learning based 3D stereo networks give superior performance compared to 2D networks and conventional stereo methods. However, this improvement in the performance comes at the…
MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching
Faranak Shamsafar, Samuel Woerz, Rafia Rahim +1
Recent methods in stereo matching have continuously improved the accuracy using deep models. This gain, however, is attained with a high increase in computation cost, such that the…
Score refinement for confidence-based 3D multi-object tracking
Nuri Benbarka, Jona Schröder, Andreas Zell
Multi-object tracking is a critical component in autonomous navigation, as it provides valuable information for decision-making. Many researchers tackled the 3D multi-object tracki…
Object detection and Autoencoder-based 6D pose estimation for highly cluttered Bin Picking
Timon Höfer, Faranak Shamsafar, Nuri Benbarka +1
Bin picking is a core problem in industrial environments and robotics, with its main module as 6D pose estimation. However, industrial depth sensors have a lack of accuracy when it…