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20202022
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cs.CV2022

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV2020

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…