Tao Wu

  • TU Munich, Department of Computer Science, Germany
  • Humboldt University of Berlin, Department of Mathematics, Germany
  • Karl Franzens University of Graz, Institute for Mathematics and Scientific Computing, Austria

According to our database1, Tao Wu authored at least 18 papers between 2011 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


Online presence:

On csauthors.net:


Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Distributed Photometric Bundle Adjustment.
Proceedings of the 8th International Conference on 3D Vision, 2020

Informative GANs via Structured Regularization of Optimal Transport.
CoRR, 2019

Probabilistic Discriminative Learning with Layered Graphical Models.
CoRR, 2019

Variational Uncalibrated Photometric Stereo Under General Lighting.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Optimization of Inf-Convolution Regularized Nonconvex Composite Problems.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

LED-Based Photometric Stereo: Modeling, Calibration and Numerical Solution.
J. Math. Imaging Vis., 2018

Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform.
CoRR, 2018

Combinatorial Preconditioners for Proximal Algorithms on Graphs.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Optimal Selection of the Regularization Function in a Weighted Total Variation Model. Part II: Algorithm, Its Analysis and Numerical Tests.
J. Math. Imaging Vis., 2017

Semi-calibrated Near-Light Photometric Stereo.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2017

A Non-convex Variational Approach to Photometric Stereo under Inaccurate Lighting.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Limiting Aspects of Nonconvex TV<sup>φ</sup> Models.
SIAM J. Imaging Sci., 2015

Robust Principal Component Pursuit via Inexact Alternating Minimization on Matrix Manifolds.
J. Math. Imaging Vis., 2015

A superlinearly convergent <i>R</i>-regularized Newton scheme for variational models with concave sparsity-promoting priors.
Comput. Optim. Appl., 2014

Nonconvex TV<sup>q</sup>-Models in Image Restoration: Analysis and a Trust-Region Regularization-Based Superlinearly Convergent Solver.
SIAM J. Imaging Sci., 2013

A Smoothing Descent Method for Nonconvex TV $$^q$$ -Models.
Proceedings of the Efficient Algorithms for Global Optimization Methods in Computer Vision, 2011