FlowBrush: Optical Flow Art. Symposium on Computational Aesthetics, Sketch-Based Interfaces and Modeling, and Non-Photorealistic Animation and Rendering (EXPRESSIVE, co-located with SIGGRAPH)., 1:1-1:9, 2017. [PUMA: 2017 B01 B04 from:mueller sfbtrr161 vis(us) vis-is visus visus:bruhnas visus:kurzhako visus:stollml visus:weiskopf] URL
PDE-based vs. Variational Methods for Perspective Shape from Shading. 2017. [PUMA: 2017 vis(us) vis-is visus:juyl] URL
Variational Large Displacement Optical Flow without Feature Matches. In E. Hancock, and M. Pelillo (Eds.), Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science, Springer, 2017. [PUMA: 2017 vis(us) vis-is visus:bruhnas visus:maurerdl visus:stollml]
Illumination-Aware Large Displacement Optical Flow. In E. Hancock, and M. Pelillo (Eds.), Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science, Springer, 2017. [PUMA: 2017 vis(us) vis-is visus:bruhnas visus:maurerdl visus:stollml visus:volzsn]
A Time-Efficient Optimisation Framework for Parameters of Opitical Flow Methods. In R. Jenssen, P. Sharma, and F. M. Bianchi (Eds.), Proceedings of Scandinavian Conference on Image Analysis (SCIA). Lecture Notes in Computer Science, (10269)Springer, 2017. [PUMA: 2017 vis(us) vis-is visus:bruhnas visus:maurerdl visus:stollml visus:volzsn]
Order-Adaptive Regularisation for Variational Optical Flow: Global, Local and in Between. In A.-B. Dahl, Y. Dong, and F. Lauze (Eds.), Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Lecture Notes in Computer Science, (10302)Springer, 2017. [PUMA: 2017 vis(us) vis-is visus:bruhnas visus:maurerdl visus:stollml]
A Comparison of Isotropic and Anisotropic Second Order Regularisers for Optical Flow. In A.-B. Dahl, Y. Dong, and F. Lauze (Eds.), Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM). Lecture Notes in Computer Science, (10302)Springer, 2017. [PUMA: 2017 vis(us) vis-is visus:bruhnas visus:maurerdl visus:stollml visus:volzsn]
Order-Adaptive and Illumination-Aware Variational Optical Flow Refinement. Proceedings of the British Machine Vision Conference (BMVC), BMVA Press, 2017. [PUMA: 2017 vis(us) vis-is visus:bruhnas visus:maurerdl visus:stollml]
FlowBrush: Optical Flow Art. Proceedings of Computational Aesthetics 2017, 2017. [PUMA: 2017 sfbtrr161 vis(us) vis-is visus visus:bruhnas visus:kurzhako visus:stollml visus:weiskopf] URL
Combining shape from shading and stereo: a variational approach for the joint estimation of depth, illumination and albedo.. Proceedings of the British Machine Vision Conference (BMVC), BMVA Press, 2016. [PUMA: 2016 vis(us) vis-is visus:bruhnas visus:juyl visus:maurerdl]
Efficient Algorithms for Global Optimisation Methods in Computer Vision (Dagstuhl Seminar 11471).. 2011. [PUMA: 2011 vis(us) vis-is visus:bruhnas]
Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461).. 2015. [PUMA: 2015 vis(us) vis-is visus:bruhnas]
Compression based pattern recognition. 2012. [PUMA: 2012 vis(us) vis-gis vis-is visus:klenksn]
Cyclic Schemes for PDE-based Image Analysis. International Journal of Computer Vision, (118)32016. [PUMA: 2016 vis(us) vis-is visus:bruhnas]
Direct Variational Perspective Shape from Shading with Cartesian Depth Parametrisation. In M. Breuß, P. Maragos, and S. Wuhrer (Eds.), Perspectives on Shape From Shading. Mathematics and Visualization, Springer, 2016. [PUMA: 2016 vis(us) vis-is visus:bruhnas visus:juyl visus:maurerdl]
An Efficient Linearisation Approach for Variational Perspective Shape from Shading. In J. Gall, P. Gehler, and B. Leibe (Eds.), German Conference on Pattern Recognition (GCPR 2015). Lecture Notes in Computer Science, (9358)Springer, 2015. [PUMA: 2015 vis(us) vis-is visus:bruhnas visus:juyl visus:maurerdl] URL
Variational Perspective Shape from Shading. In J.-F. Aujol, M. Nikolova, and N. Papadakis (Eds.), Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2015). Lecture Notes in Computer Science, Springer, 2015. [PUMA: 2015 vis(us) vis-is visus:bruhnas visus:juyl]
Learning Brightness Transfer Functions for the Joint Recovery of Illumination Changes and Optical Flow. In D. Fleet, T. Pajdla, B. Schiele, and T. Tuytelaars (Eds.), Proceedings of European Conference on Computer Vision (ECCV 2014). Lecture Notes in Computer Science, (8689)Springer, 2014. [PUMA: 2014 vis(us) vis-is visus:bruhnas visus:stollml visus:volzsn] URL
State-of-the-Art of Visualization for Eye Tracking Data. EuroVis STAR, 2014. [PUMA: 2014 vis(us) vis-gis vis-is visus visus:blaschta visus:burchml visus:ertl visus:kurzhako visus:raschkml visus:weiskopf] URL
Understanding, optimising, and extending data compression with anisotropic diffusion. International Journal of Computer Vision, (108)32014. [PUMA: 2014 vis(us) vis-is visus:bruhnas] URL