6 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…
FourierMask: Instance Segmentation using Fourier Mapping in Implicit Neural Networks
Hamd ul Moqeet Riaz, Nuri Benbarka, Timon Hoefer +1
We present FourierMask, which employs Fourier series combined with implicit neural representations to generate instance segmentation masks. We apply a Fourier mapping (FM) to the c…
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…
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…
FourierNet: Compact mask representation for instance segmentation using differentiable shape decoders
Hamd ul Moqeet Riaz, Nuri Benbarka, Andreas Zell
We present FourierNet, a single shot, anchor-free, fully convolutional instance segmentation method that predicts a shape vector. Consequently, this shape vector is converted into…