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Position: |
Former Research Assistant |
E-mail: |
hafner -at- mia.uni-saarland.de
(please replace anti-spam -at- by @)
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- Computer Vision (Stereo, Optic Flow, ...)
- Image Fusion (Exposure Fusion, Focus Fusion, ...)
- High Dynamic Range Imaging
- Optimisation
Journal Papers
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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.
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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.
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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.
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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.
Conference Papers
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
Technical Reports
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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.
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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.
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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.
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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.
Theses
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D. Hafner: Census-Based Variational Optic Flow.
M.Sc. Thesis in Computer Science,
Saarland University, Saarbrücken, Germany, October 2012.
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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
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Michel Biertz: M.Sc. Thesis in Visual Computing.
(in progress)
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Madina Mustafina: PatchMatch for Large Displacement Optic Flow Estimation without Warping.
M.Sc. Thesis in Computer Science,
Saarland University, Saarbrücken, Germany, July 2016.
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Maria Luschkova: Exposure Fusion for Dynamic Scenes.
M.Sc. Thesis in Visual Computing,
Saarland University, Saarbrücken, Germany, August 2013.
Bachelor's Theses Advisor
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Edgar Tretschk: B.Sc. Thesis in Computer Science.
(in progress)
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Karina Kolinsky: Automatic Protein Detection.
B.Sc. Thesis in Computer Science,
Saarland University, Saarbrücken, Germany, June 2016.
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Jan Contelly: Gradient Domain Tone Mapping.
B.Sc. Thesis in Computer Science,
Saarland University, Saarbrücken, Germany, August 2013.
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