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Technical University of Munich

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Journal Articles
2018
[]Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform (L. Ma, J. Stueckler, T. Wu and D. Cremers), In , 2018. ([arxiv]) [bibtex]
[]LED-based Photometric Stereo: Modeling, Calibration and Numerical Solution (Y. Quéau, B. Durix, T. Wu, D. Cremers, F. Lauze and J.-D. Durou), In Journal of Mathematical Imaging and Vision, volume 60, 2018. ([arxiv],[codes]) [bibtex] [doi] [pdf]
Conference and Workshop Papers
2020
[]Distributed Photometric Bundle Adjustment (N Demmel, M Gao, E Laude, T Wu and D Cremers), In International Conference on 3D Vision (3DV), 2020. ([project page][code]) [bibtex] [pdf]Oral Presentation
[]Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning (Z. Ye, T. Möllenhoff, T. Wu and D. Cremers), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. ([code]) [bibtex] [pdf]
2019
[]Informative GANs via Structured Regularization of Optimal Transport (P. Bréchet, T. Wu, T. Möllenhoff and D. Cremers), In NeurIPS Workshop on Optimal Transport and Machine Learning, 2019.  [bibtex] [arXiv:1912.02160]
[]Optimization of Inf-Convolution Regularized Nonconvex Composite Problems (E. Laude, T. Wu and D. Cremers), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.  [bibtex] [pdf]
[]Variational Uncalibrated Photometric Stereo under General Lighting (B. Haefner, Z. Ye, M. Gao, T. Wu, Y. Quéau and D. Cremers), In International Conference on Computer Vision (ICCV), 2019. ([supp] [poster] [code] [cvf] [ieeexplore]) [bibtex] [arXiv:1904.03942] [pdf]
2018
[]Combinatorial Preconditioners for Proximal Algorithms on Graphs (T. Möllenhoff, Z. Ye, T. Wu and D. Cremers), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.  [bibtex] [pdf]
[]A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization (E. Laude, T. Wu and D. Cremers), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.  [bibtex] [pdf]
2017
[]A Non-Convex Variational Approach to Photometric Stereo under Inaccurate Lighting (Y. Quéau, T. Wu, F. Lauze, J.-D. Durou and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. ([codes]) [bibtex] [pdf]
[]Semi-Calibrated Near-Light Photometric Stereo (Y. Quéau, T. Wu and D. Cremers), In International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 2017. ([codes]) [bibtex] [pdf]
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Teaching

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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News

04.06.2021

Bernt Schiele (Max Planck Institute for Informatics) will give a talk in the TUM AI lecture series on June 10th, 3pm! Livestream

05.05.2021
French-German Machine Learning Symposium

French-German Machine Learning Symposium

The French-German Machine Learning Symposium aims to strengthen interactions and inspire collaborations between both countries. We invited some of the leading ML researchers from France and Germany to this two-day symposium to give a glimpse into their research, and engage in discussions on the future of machine learning and how to strengthen research collaborations in ML between France and Germany.

The list of speakers includes Yann LeCun, Cordelia Schmid, Jean-Bernard Lasserre, Bernhard Schölkopf, and many more! For the full program please visit the webpage.

03.05.2021

Ron Kimmel (Technion - Israel Institute of Technology) will give a talk in the TUM AI lecture series on May 6th, 3pm! Livestream

23.04.2021

4Seasons Dataset: We have released a novel dataset for benchmarking multi-weather SLAM in autonomous driving.

19.04.2021

Hao Li (Pinscreen) will give a talk in the TUM AI lecture series on April 22nd, 8pm! Livestream

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