Best Poster Award, Deutsche Gesellschaft für Essstörungen (DGESS), 2018, Körper Sprache: Sprachliche Repräsentation von Körpern bei Patientinnen und Patienten mit Essstörungen, by Walder L., Quiros-Ramirez M.A., Mohler B., Black M.J., Keizer A., Zipfel S., Giel K., Mölbert S. - More Information Betty Mohler Michael Black Simone Mölbert
Andreas Geiger with collaborators from Daimler and Freiburg won the best student paper award at 3DV for the paper "Sparsity Invariant CNNs"
Siyu Tang: Winner of the CVPR 2017 Multi-Object Tracking Challenge
Highly cited article: "A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles Behind Them" by Deqing Sun, Stefan Roth, and Michael Black, is cited by Thompson Reuters as one of three highly cited articles published in the Int. J. of Computer Vision (IJCV) since 2014.
Michael Black Deqing Sun
The FAUST dataset was awarded the "Dataset Award" at the Eurographics Symposium on Geometry Processing 2016. The award encourages and recognises the importance of the distribution of high-quality datasets on which geometry processing algorithms are tested. The creators of the dataset are Federica Bogo, Javier Romero, Matthew Loper, and Michael Black. The work originally appeared in the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2014.
Federica Bogo Matthew Loper Michael Black
The Middlebury Dataset was awarded the 2015 IEEE Mark Everingham Prize for service and contributions to the computer vision community. Michael Black was part of the team behind the optical flow benchmark. Michael Black
Jonas Wulff. Outstanding Reviewer Award. ICCV 2015.
Ali Osman Ulusoy, Andreas Geiger, and Michael J. Black. Best Paper Award, International Conference on 3D Vision (3DV), 2015, for the paper "Towards Probabilistic Volumetric Reconstruction using Ray Potentials."
Osman Ulusoy Andreas Geiger Michael Black
Gerard Pons-Moll: BMVC 2013Best Science Paper for Metric Regression Forests for Human Pose Estimation with Jonathan Taylor, Jamie Shotton, Aaron Hertzmann and Andrew Fitzgibbon. - More Information Gerard Pons-Moll
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems