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Michael Stoll
Michael Stoll
Verified email at vis.uni-stuttgart.de - Homepage
Title
Cited by
Cited by
Year
Adaptive integration of feature matches into variational optical flow methods
M Stoll, S Volz, A Bruhn
Computer Vision–ACCV 2012: 11th Asian Conference on Computer Vision, Daejeon …, 2013
392013
Learning brightness transfer functions for the joint recovery of illumination changes and optical flow
O Demetz, M Stoll, S Volz, J Weickert, A Bruhn
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
362014
Order-Adaptive and Illumination-Aware Variational Optical Flow Refinement.
D Maurer, M Stoll, A Bruhn
BMVC, 2017
222017
A time-efficient optimisation framework for parameters of optical flow methods
M Stoll, S Volz, D Maurer, A Bruhn
Image Analysis: 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway …, 2017
112017
Joint trilateral filtering for multiframe optical flow
M Stoll, S Volz, A Bruhn
2013 IEEE International Conference on Image Processing, 3845-3849, 2013
102013
Racecar tracking and its visualization using sparse data
M Stoll, R Krüger, T Ertl, A Bruhn
Proc. Workshop on Sports Data Visualization, 2013
102013
A comparison of isotropic and anisotropic second order regularisers for optical flow
D Maurer, M Stoll, S Volz, P Gairing, A Bruhn
Scale Space and Variational Methods in Computer Vision: 6th International …, 2017
72017
Order-adaptive regularisation for variational optical flow: Global, local and in between
D Maurer, M Stoll, A Bruhn
Scale Space and Variational Methods in Computer Vision: 6th International …, 2017
72017
Visual analytics and annotation of pervasive eye tracking video
K Kurzhals, N Rodrigues, M Koch, M Stoll, A Bruhn, A Bulling, D Weiskopf
ACM Symposium on Eye Tracking Research and Applications, 1-9, 2020
62020
Directional Priors for Multi-Frame Optical Flow.
D Maurer, M Stoll, A Bruhn
BMVC, 106, 2018
42018
Data challenges in variational optical flow
M Stoll
12020
Variational large displacement optical flow without feature matches
M Stoll, D Maurer, A Bruhn
Energy Minimization Methods in Computer Vision and Pattern Recognition: 11th …, 2018
12018
LUKe and MIKe: learning from user knowledge and managing interactive knowledge extraction
S Metzger, M Stoll, K Hose, R Schenkel
Proceedings of the 21st ACM international conference on Information and …, 2012
12012
Illumination-Aware Large Displacement Optical Flow
M Stoll, D Maurer, S Volz, A Bruhn
Energy Minimization Methods in Computer Vision and Pattern Recognition: 11th …, 2018
2018
FlowBrush: optical flow art
K Kurzhals, M Stoll, A Bruhn, D Weiskopf
Proceedings of the symposium on Computational Aesthetics, 1-9, 2017
2017
MIKE-Managing Interactive Knowlegde Extraction
M Stoll
Universität des Saarlandes Saarbrücken, 2012
2012
of Proceedings: LWA 2011: Technical Report; Report of the symposium" Lernen, Wissen, Adaptivität 2011" of the GI special interest groups KDML, IR and WM
M Stoll, K Hose, S Metzger, R Schenkel
Otto von Guericke Universität, 2011
2011
Interaktive Wissensextraktion und Wissenssuche.
M Stoll, K Hose, S Metzger, R Schenkel
LWA, 205-206, 2011
2011
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