Niklas Kaemper
Position: Research Assistant
E-mail: kaemper -at- mia.uni-saarland.de
(please replace anti-spam -at- by @)
Address: Mathematical Image Analysis Group
Faculty of Mathematics and Computer Science,
Saarland University
Campus E1.7
66041 Saarbrücken, Germany
Office: Room 4.02
Building E1.7, Saarbrücken Campus
see also Contact
Research Area

Publications

Conference Papers

  1. K. Schrader, P. Peter, N. Kämper, J. Weickert:
    Efficient neural generation of 4K masks for homogeneous diffusion inpainting.
    In L. Calatroni, M. Donatelli, S. Morigi, M. Prato, M. Santavesaria (Eds.): Scale Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 14009, Springer, Cham, 16-28, 2023.
    Also available as arXiv:2303.10096 [eess.IV], March 2023.

  2. N. Kämper, J. Weickert:
    Domain decomposition algorithms for real-time homogeneous diffusion inpainting in 4K.
    Proc. 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022, Singapore, May 2022), 1680-1684, 2022.
    Also available as arXiv:2110.03946 [eess.IV], revised February 2022.

    3. Preprints

  3. N. Kämper, V. Chizhov, J. Weickert:
    Efficient Parallel Data Optimization for Homogeneous Diffusion Inpainting of 4K Images.
    arXiv:2401.06747 [eess.IV], revised August 2024.

  4. N. Kämper, V. Chizhov, J. Weickert:
    Efficient Parallel Algorithms for Inpainting-Based Representations of 4K Images - Part I: Homogeneous Diffusion Inpainting.
    arXiv:2401.06744 [eess.IV], January 2024.

    5. Theses

  5. N. Kämper:
    Neural Decoding for RJIP.
    Master's Thesis in Visual Computing,
    Saarland University, Saarbrücken, Germany, November 2020.

  6. N. Kämper:
    Encoding Strategies for Pixel Data in PDE-based Compression.
    Bachelor's Thesis in Computer Science,
    Saarland University, Saarbrücken, Germany, January 2019.