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Vorträge

Robust Discrimination and Generation of Faces using Compact, Disentangled Embeddings

Talk
  • 22 August 2019 • 15:00 16:00
  • Björn Browatzki
  • PS Aquarium

Current solutions to discriminative and generative tasks in computer vision exist separately and often lack interpretability and explainability. Using faces as our application domain, here we present an architecture that is based around two core ideas that address these issues: first, our framework learns an unsupervised, low-dimensional embedding of faces using an adversarial autoencoder that is able to synthesize high-quality face images. Second, a supervised disentanglement splits the low-dimensional embedding vector into four sub-vectors, each of which contains separated information about one of four major face attributes (pose, identity, expression, and style) that can be used both for discriminative tasks and for manipulating all four attributes in an explicit manner. The resulting architecture achieves state-of-the-art image quality, good discrimination and face retrieval results on each of the four attributes, and supports various face editing tasks using a face representation of only 99 dimensions. Finally, we apply the architecture's robust image synthesis capabilities to visually debug label-quality issues in an existing face dataset.

Organizers: Timo Bolkart


  • Prof. Dr. Dawn Bonnell
  • MPI-IS, Stuttgart, Lecture Hall 2 D5

With the ubiquity of catalyzed reactions in manufacturing, the emergence of the device laden internet of things, and global challenges with respect to water and energy, it has never been more important to understand atomic interactions in the functional materials that can provide solutions in these spaces.

Organizers: Katherine J. Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler


  • Prof. Dr. Thomas Ertl
  • MPI-IS, Stuttgart, Lecture Hall 2 D5

Big Data has become the general term relating to the benefits and threats which result from the huge amount of data collected in all parts of society. While data acquisition, storage and access are relevant technical aspects, the analysis of the collected data turns out to be at the core of the Big Data challenge. Automatic data mining and information retrieval techniques have made much progress but many application scenarios remain in which the human in the loop plays an essential role. Consequently, interactive visualization techniques have become a key discipline of Big Data analysis and the field is reaching out to many new application domains. This talk will give examples from current visualization research projects at the University of Stuttgart demonstrating the thematic breadth of application scenarios and the technical depth of the employed methods. We will cover advances in scientific visualization of fields and particles, visual analytics of document collections and movement patterns as well as cognitive aspects.

Organizers: Katherine J. Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler


  • Carl E. Rasmussen
  • MPI IS Lecture Hall Tübingen

Gaussian Processes are a principled, practical, probabilistic approach to learning in flexible non-parametric models and have found numerous applications in regression, classification, unsupervised learning and reinforcement learning. Inference, learning and prediction can be done exactly on small data sets with Gaussian likelihood. In more realistic application with large scale data and more complicated likelihoods approximations are necessary. The variational framework for approximate inference in Gaussian processes has emerged recently as a highly effective and practical tool. I will review and demonstrate the capabilities of this framework applied to non-linear state space models.

Organizers: Philipp Hennig


  • Weiqiang Chen Ph.D.
  • Stuttgart

Taking advantages of state-of-art micro/nanotechnologies, fascinating functional biomaterials and integrated biosystems, we can address numerous important problems in fundamental biology as well as clinical applications in cancer diagnosis and treatment.

Organizers: Peer Fischer


  • Robin Thandiackal
  • 2P4, Stuttgart MPI IS

Exciting talk on modeling anguilliform swimming, robotic testing.

Organizers: Steve Heim Alexander Badri-Sprowitz


  • Zeynep Akata
  • S2.014

Clearly explaining a rationale for a classification decision to an end-user can be as important as the decision itself. Existing approaches for deep visual recognition are generally opaque and do not output any justification text; contemporary vision-language models can describe image content but fail to take into account class-discriminative image aspects which justify visual predictions. In this talk, I will present my past and current work on Zero-Shot Learning, Vision and Language for Generative Modeling and Explainable Artificial Intelligence in that (1) how we can generalize the image classification models to the cases when no visual training data is available, (2) how to generate images and image features using detailed visual descriptions, and (3) how our models focus on discriminating properties of the visible object, jointly predict a class label,explain why the predicted label is appropriate for the image whereas another label is not.

Organizers: Andreas Geiger


Structure-Aware Shape Synthesis

Talk
  • 03 July 2018 • 11:00 12:00
  • Elena Balashova (Sizikova)
  • Aquarium N3

Complex shapes can can be summarized using a coarsely defined structure which is consistent and robust across variety of observations. However, existing synthesis techniques do not consider structural decomposition during synthesis, causing generation of implausible or structurally unrealistic shapes. We explore how structure-aware reasoning can benefit existing generative techniques for complex 2D and 3D shapes. We evaluate our methodology on a 3D dataset of chairs and a 2D dataset of typefaces.

Organizers: Sergi Pujades


The Computational Skin. Tactile Perception based on Slip Movements.

IS Colloquium
  • 02 July 2018 • 14:30 15:30
  • Prof. Dr. Cornelius Schwarz
  • MPI-IS Stuttgart, Heisenbergstr. 3, Room 2P4

Touch requires mechanical contact and is governed by the physics of friction. Frictional movements may convert the continuous 3D profile of textural objects into discrete and probabilistic movement events of the viscoelastic integument (skin/hair) called stick-slip movements (slips). This complex transformation may further be determined by the microanatomy and the active movements of the sensing organ. Thus, the integument may realize a computation, transforming the tactile world in a context dependent way - long before it even activates neurons. The possibility that the tactile world is perceived through these ‘fractured goggles’ of friction has been largely ignored by classical perceptual and neuro-scientific work. I will present biomechanical, neuro-scientific, and behavioral work supporting the slip hypothesis.

Organizers: Katherine J. Kuchenbecker


  • Prof. William W. Hager
  • AMD seminar room (N2.025)

Optimal control problems are often too complex to solve analytically. Computational methods usually replace the continuous infinite dimensional problem by a finite dimensional discrete approximation. The talk will survey classical discretization techniques based on a Runge-Kutta approximation to the differential equations (an h-method) and then introduce recent approximations based on collocation at the roots of orthogonal polynomials (a p-method). The best approximations are often achieved using an hp-framework that combines the best features of both approaches. Numerical results using the GPOPS-II (General Pseudospectral Optimal Control Software package) will be presented.

Organizers: Jia-Jie Zhu