Dr.

David Hafner

Former Ph.D. Student


Position:    Former Ph.D. Student
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  • Computer Vision (Stereo, Optic Flow, ...)
  • Image Fusion (Exposure Fusion, Focus Fusion, ...)
  • High Dynamic Range Imaging
  • Optimisation

    Journal Papers

  1. D. Hafner, J. Weickert:
    Variational image fusion with optimal local contrast.
    Computer Graphics Forum, Vol. 35, No. 1, 100-112, February 2016.
    Revised version of Technical Report No. 360, Department of Mathematics, Saarland University, Saarbrücken, Germany, April 2015.
    See also: Supplementary Material Webpage.

  2. M. Boshtayeva, D. Hafner, J. Weickert:
    A focus fusion framework with anisotropic depth map smoothing.
    Pattern Recognition, Vol. 48, No. 11, 3310-3323, November 2015.
    Invited Paper.
    Revised version of Technical Report No. 343, Department of Mathematics, Saarland University, Saarbrücken, Germany, February 2014.

  3. O. Demetz, D. Hafner, J. Weickert:
    Morphologically invariant matching of structures with the complete rank transform.
    International Journal of Computer Vision, Vol. 113, No. 3, 220-232, July 2015.
    Invited Paper.
    Revised version of Technical Report No. 348, Department of Mathematics, Saarland University, Saarbrücken, Germany, May 2014.

  4. D. Hafner, O. Demetz, J. Weickert, M. Reißel:
    Mathematical foundations and generalisations of the census transform for robust optic flow computation.
    Journal of Mathematical Imaging and Vision, Vol. 52, No. 1, 71-86, May 2015.
    Invited Paper.
    Revised version of Technical Report No. 337, Department of Mathematics, Saarland University, Saarbrücken, Germany, October 2013.

  5. Conference Papers

  6. D. Hafner, P. Ochs, J. Weickert, M. Reißel, S. Grewenig:
    FSI schemes: Fast semi-iterative solvers for PDEs and Optimisation Methods.
    In B. Andres, B. Rosenhahn (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 9796, 91-102, Springer, Cham, 2016.
    Awarded the GCPR 2016 Best Paper Award.

  7. D. Hafner, C. Schroers, J. Weickert:
    Introducing maximal anisotropy into second order coupling models.
    In J. Gall, P. Gehler, B. Leibe (Eds.): Pattern Recognition. Lecture Notes in Computer Science, Vol. 9358, 79-90, Springer, Berlin, 2015.

  8. C. Schroers, D. Hafner, J. Weickert:
    Multiview depth parameterisation with second order regularisation.
    In J.-F. Aujol, M. Nikolova, N. Papadakis (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 9087, 551-562, Springer, Berlin, 2015.

  9. D. Hafner, J. Weickert:
    Variational exposure fusion with optimal local contrast.
    In J.-F. Aujol, M. Nikolova, N. Papadakis (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 9087, 425-436, Springer, Berlin, 2015.

  10. D. Hafner, O. Demetz, J. Weickert:
    Simultaneous HDR and optic flow computation.
    Proc. 22nd International Conference on Pattern Recognition (ICPR 2014, Stockholm, Sweden, August 2014), 2065-2070, IEEE Computer Society Press, 2014.

  11. O. Demetz, D. Hafner, J. Weickert:
    The complete rank transform: A tool for accurate and morphologically invariant matching of structures.
    In T. Burghardt, D. Damen, W. Mayol-Cuevas and M. Mirmehdi: Proc. 24th British Machine Vision Conference, BMVA Press, 2013.
    Awarded the Maria Petrou Prize for Invariance in Computer Vision.

  12. M. Boshtayeva, D. Hafner, J. Weickert:
    Focus fusion with anisotropic depth map smoothing.
    In A. Bors, E. Hancock, W. Smith, R. Wilson (Eds.): Computer Analysis of Images and Patterns. Lecture Notes in Computer Science, Vol. 8048, 67-74, Springer, Berlin, 2013.

  13. D. Hafner, O. Demetz, J. Weickert:
    Why is the census transform good for robust optic flow computation?
    In A. Kuijper, T. Pock, K. Bredies, H. Bischof (Eds.): Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 7893, 210-221, Springer, Berlin, 2013.

  14. Technical Reports

  15. D. Hafner, J. Weickert:
    Variational Image Fusion with Optimal Local Contrast.
    Technical Report No. 360, Department of Mathematics, Saarland University, Saarbrücken, Germany, April 2015.
    See also: Supplementary Material Webpage.
  16. O. Demetz, D. Hafner, J. Weickert:
    Morphologically Invariant Matching of Structures with the Complete Rank Transform.
    Technical Report No. 348, Department of Mathematics, Saarland University, Saarbrücken, Germany, May 2014.

  17. M. Boshtayeva, D. Hafner, J. Weickert:
    A Focus Fusion Framework with Anisotropic Depth Map Smoothing.
    Technical Report No. 343, Department of Mathematics, Saarland University, Saarbrücken, Germany, February 2014.

  18. D. Hafner, O. Demetz, J. Weickert, M. Reißel:
    Mathematical Foundations and Generalisations of the Census Transform for Robust Optic Flow Computation.
    Technical Report No. 337, Department of Mathematics, Saarland University, Saarbrücken, Germany, October 2013.

  19. Theses

  20. D. Hafner: Census-Based Variational Optic Flow.
    M.Sc. Thesis in Computer Science,
    Saarland University, Saarbrücken, Germany, October 2012.

  21. D. Hafner: Evaluation flussbasierter Ansätze zur 3D-Szenen-Modellierung aus Bildsequenzen im lateralen Fahrzeugumfeld.
    B.Eng. Thesis in Information Technology (IT-Automotive),
    DHBW Stuttgart, Stuttgart, Germany, September 2010.

    Master's Theses Advisor

  1. Michel Biertz: M.Sc. Thesis in Visual Computing.
    (in progress)

  2. Madina Mustafina: PatchMatch for Large Displacement Optic Flow Estimation without Warping.
    M.Sc. Thesis in Computer Science,
    Saarland University, Saarbrücken, Germany, July 2016.

  3. Maria Luschkova: Exposure Fusion for Dynamic Scenes.
    M.Sc. Thesis in Visual Computing,
    Saarland University, Saarbrücken, Germany, August 2013.

    Bachelor's Theses Advisor

  1. Edgar Tretschk: B.Sc. Thesis in Computer Science.
    (in progress)

  2. Karina Kolinsky: Automatic Protein Detection.
    B.Sc. Thesis in Computer Science,
    Saarland University, Saarbrücken, Germany, June 2016.

  3. Jan Contelly: Gradient Domain Tone Mapping.
    B.Sc. Thesis in Computer Science,
    Saarland University, Saarbrücken, Germany, August 2013.




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