2 citations · 4 across the 5 of their papers we have counts for
8 papers
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning
Zhenzhang Ye, Thomas Möllenhoff, Tao Wu +1
Structured convex optimization on weighted graphs finds numerous applications in machine learning and computer vision. In this work, we propose a novel adaptive preconditioning str…
Informative GANs via Structured Regularization of Optimal Transport
Pierre Bréchet, Tao Wu, Thomas Möllenhoff +1
We tackle the challenge of disentangled representation learning in generative adversarial networks (GANs) from the perspective of regularized optimal transport (OT). Specifically,…
Variational Uncalibrated Photometric Stereo under General Lighting
Bjoern Haefner, Zhenzhang Ye, Maolin Gao +3
Photometric stereo (PS) techniques nowadays remain constrained to an ideal laboratory setup where modeling and calibration of lighting is amenable. To eliminate such restrictions,…
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems
Emanuel Laude, Tao Wu, Daniel Cremers
In this work, we consider nonconvex composite problems that involve inf-convolution with a Legendre function, which gives rise to an anisotropic generalization of the proximal mapp…
Probabilistic Discriminative Learning with Layered Graphical Models
Yuesong Shen, Tao Wu, Csaba Domokos +1
Probabilistic graphical models are traditionally known for their successes in generative modeling. In this work, we advocate layered graphical models (LGMs) for probabilistic discr…
Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform
Lingni Ma, Jörg Stückler, Tao Wu +1
Dense pixelwise prediction such as semantic segmentation is an up-to-date challenge for deep convolutional neural networks (CNNs). Many state-of-the-art approaches either tackle th…