I continue to collaborate with MPI-PS and I am an affilated researcher. This website however is not up to date.
Lectures take place at the University of Tübingen and can be attended by all Master and PhD students of the University and MPI Tübingen.
The lab for computer vision at the Max Planck for Informatics in Saarbrücken has 2 Open PhD positions on the areas of
Candidates should have:
PhD students will work on cutting edge research at the intersection between vision, graphics and learning. Research will require knowledge of deep learning, geometry processing and computer vision.
Open positions for research internships on similar areas as above. Research interns are typically enrolled in a PhD program and stay for 6 months.
Contact me for details.
Statistical shape models enable the inference of object shape from incomplete, noisy, ambiguous 2D or 3D data. Training such models requires precisely registering a corpus of 3D scans with a common 3D template.
Registering a template mesh to 3D scans is challenging \cite{Hirshberg:BST:11}. Scans&nb...
Michael Black Matthew Loper Javier Romero Aggeliki Tsoli Federica Bogo David Hirshberg Eric Rachlin Alex Weiss Gerard Pons-Moll
Human bodies are dynamic; they deform as they move, jiggle due to soft-tissue dynamics, and change shape with respiration. In \cite{Tsoli:SIGGRAPH:2014} we learn a model of body shape deformations due to breathing for different breathing types and provide simple animation controls to render lifelike br...
Gerard Pons-Moll Javier Romero Naureen Mahmood Matthew Loper Aggeliki Tsoli Michael Black
While multi-camera video data facilitates markerless motion capture, many challenges remain.
We formulate the problem of 3D human pose estimation and tracking as inference in a graphical model \cite{Sigal:IJCV:11}. The body is modeled as a c...
A prior over human pose is important for many human tracking and pose estimation problems.
We introduce a sparse Bayesian network model of human pose that is non-parametric with respect to the estimation of ...
Peter Vincent Gehler
Andreas Lehrmann
Ijaz Akhter
Michael Black
Gerard Pons-Moll
Søren Hauberg
Jürgen Gall
The human body is certainly central to our lives and is commonly depicted in images and video. We are developing the world's most realistic models of the body by learning their shape and how they move from data. Our goal is to make 3D models of the body look and move in ways that make them indistinguishable from real human...
Michael Black Javier Romero Matthew Loper Gerard Pons-Moll Naureen Mahmood Federica Bogo
The estimation of 3D human pose from 2D images is inherently ambiguous. To that end, we develop inference methods and human pose models that enable prediction of 3D pose from images. Learned models of human pose rely on training data but we find that existing motion capture datasets are too limited to explore the full rang...
Clothed virtual characters in varied sizes and shapes are necessary for film, gaming, and on-line fashion applications. Dressing such characters is a significant bottleneck, requiring manual effort to design clothing, position it on the body, and simulate its physical deformation. Our goal is to do for clothing ...
Lassner, C., Pons-Moll, G., Gehler, P. V.
In Proceedings IEEE International Conference on Computer Vision (ICCV), IEEE, Piscataway, NJ, USA, IEEE International Conference on Computer Vision (ICCV), October 2017 (inproceedings)
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Bogo, F., Romero, J., Pons-Moll, G., Black, M. J.
In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (inproceedings)
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Zhang, C., Pujades, S., Black, M., Pons-Moll, G.
In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017, Spotlight (inproceedings)
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Kim, M., Pons-Moll, G., Pujades, S., Bang, S., Kim, J., Black, M., Lee, S.
ACM Transactions on Graphics, (Proc. SIGGRAPH), 36(4), 2017 (article)
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(Best Paper, Eurographics 2017)
Marcard, T. V., Rosenhahn, B., Black, M., Pons-Moll, G.
Computer Graphics Forum 36(2), Proceedings of the 38th Annual Conference of the European Association for Computer Graphics (Eurographics), pages: 349-360 , 2017 (article)
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Pons-Moll, G., Pujades, S., Hu, S., Black, M.
ACM Transactions on Graphics, (Proc. SIGGRAPH), 36(4), 2017, Two first authors contributed equally (article)
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Marcard, T. V., Pons-Moll, G., Rosenhahn, B.
Transactions on Pattern Analysis and Machine Intelligence PAMI, January 2016 (article)ps
Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M. J.
ACM Trans. Graphics (Proc. SIGGRAPH Asia), 34(6):248:1-248:16, ACM, New York, NY, October 2015 (article)
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Pons-Moll, G., Romero, J., Mahmood, N., Black, M. J.
ACM Transactions on Graphics, (Proc. SIGGRAPH), 34(4):120:1-120:14, ACM, August 2015 (article)
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Pons-Moll, G., Taylor, J., Shotton, J., Hertzmann, A., Fitzgibbon, A.
International Journal of Computer Vision, pages: 1-13, 2015 (article)ps
Pons-Moll, G., Fleet, D. J., Rosenhahn, B.
In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 2345-2352, Columbus, Ohio, USA, IEEE International Conference on Computer Vision and Pattern Recognition, June 2014 (inproceedings)
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(Best Science Paper Award)
Pons-Moll, G., Taylor, J., Shotton, J., Hertzmann, A., Fitzgibbon, A.
In British Machine Vision Conference (BMVC) , BMVA Press, September 2013 (inproceedings)ps
Kuznetsova, A., Pons-Moll, G., Rosenhahn, B.
In German Conference on Pattern Recognition (GCPR), August 2012 (inproceedings)ps
Leal-Taixé, L., Pons-Moll, G., Rosenhahn, B.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2012 (inproceedings)ps
Leal-Taixé, L., Pons-Moll, G., Rosenhahn, B.
In Theoretic Foundations of Computer Vision: Outdoor and Large-Scale Real-World Scene Analysis, Springer, April 2012 (incollection)ps
Pons-Moll, G., Leal-Taix’e, L., Gall, J., Rosenhahn, B.
In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 305-328, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)ps
Pons-Moll, G., Baak, A., Gall, J., Leal-Taixe, L., Mueller, M., Seidel, H., Rosenhahn, B.
In IEEE International Conference on Computer Vision (ICCV), pages: 1243-1250, November 2011 (inproceedings)ps
Leal-Taixé, L., Rosenhahn, G. P. A. B.
In IEEE International Conference on Computer Vision Workshops (IICCVW), November 2011 (inproceedings)ps
Pons-Moll, G., Leal-Taixé, L., Truong, T., Rosenhahn, B.
In German Conference on Pattern Recognition (GCPR), pages: 416-425, September 2011 (inproceedings)ps
Pons-Moll, G., Rosenhahn, B.
In Visual Analysis of Humans: Looking at People, pages: 139-170, 9, (Editors: T. Moeslund, A. Hilton, V. Krueger, L. Sigal), Springer, 2011 (inbook)ps
Baak, A., Helten, T., Müller, M., Pons-Moll, G., Rosenhahn, B., Seidel, H.
In European Conference on Computer Vision (ECCV Workshops), September 2010 (inproceedings)ps
Pons-Moll, G., Baak, A., Helten, T., Müller, M., Seidel, H., Rosenhahn, B.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2010 (inproceedings)ps
Pons-Moll, G., Rosenhahn, B.
In IEEE Workshop on Applications of Computer Vision (WACV),, December 2009 (inproceedings)ps
Pons-Moll, G., Crosas, C., Tadmor, G., MacLeod, R., Rosenhahn, B., Brooks, D.
In IEEE Computers in Cardiology (CINC), September 2009 (inproceedings)ps
Pons-Moll, G., Tadmor, G., MacLeod, R. S., Rosenhahn, B., Brooks, D. H.
In World Congress of Medical Physics and Biomedical Engineering (WC), 2009 (inproceedings)ps