activity
20152022
most citedComplex-Valued Frequency Selective Extrapolation for Fast Image and Video Signal Extrapolation

54 citations · 219 across the 34 of their papers we have counts for

collaborators

36 papers

eess.IV2022

Improving block-based compensated wavelet lifting by reconstructing unconnected pixels

Wolfgang Schnurrer, Jürgen Seiler, André Kaup

This paper presents a new approach for improving the visual quality of the lowpass band of a compensated wavelet transform. A high quality of the lowpass band is very important as…

eess.IV2022

3-D mesh compensated wavelet lifting for 3-D+t medical CT data

Wolfgang Schnurrer, Thomas Richter, Jürgen Seiler +2

For scalable coding, a high quality of the lowpass band of a wavelet transform is crucial when it is used as a downscaled version of the original signal. However, blur and motion c…

eess.IV2022

Temporal error concealment for fisheye video sequences based on equisolid re-projection

Andrea Eichenseer, Jürgen Seiler, Michel Bätz +1

Wide-angle video sequences obtained by fisheye cameras exhibit characteristics that may not very well comply with standard image and video processing techniques such as error conce…

eess.IV20222 cited

Domain Adaptation for Unknown Image Distortions in Instance Segmentation

Maximiliane Gruber, Fabian Brand, Alina Mosebach +2

Data-driven techniques for machine vision heavily depend on the training data to sufficiently resemble the data occurring during test and application. However, in practice unknown…

cs.CV2022

Synthesizing Annotated Image and Video Data Using a Rendering-Based Pipeline for Improved License Plate Recognition

Andreas Spruck, Maximilane Gruber, Anatol Maier +4

An insufficient number of training samples is a common problem in neural network applications. While data augmentation methods require at least a minimum number of samples, we prop…

cs.CV20223 cited

3D Rendering Framework for Data Augmentation in Optical Character Recognition

Andreas Spruck, Maximiliane Hawesch, Anatol Maier +3

In this paper, we propose a data augmentation framework for Optical Character Recognition (OCR). The proposed framework is able to synthesize new viewing angles and illumination sc…