Thomas Endres

Partner, TNG Consulting

In his role as a Partner for TNG Technology Consulting in Munich, Thomas Endres works as an IT consultant. Besides his normal work for the company and the customers he is creating various prototypes - like a telepresence robotics system with which you can see reality through the eyes of a robot, or an Augmented Reality AI that shows the world from the perspective of an artist. He is working on various applications in the fields of AR/VR, AI and gesture control, putting them to use e.g. in autonomous or gesture controlled drones. But he is also involved in other Open Source projects written in Java, C# and all kinds of JavaScript languages.

Thomas studied IT at the TU Munich and is passionate about software development and all the other aspects of technology. As an Intel Software Innovator and Black Belt, he is promoting new technologies like AI, AR/VR and robotics around the world. For this he received amongst others a JavaOne Rockstar award.

 

Talks on Wurreka:

What if Virtual Reality glasses could transform your environment into a three-dimensional work of art in realtime? What if every detail of the world would be shown in the style of a painting from Van Gogh? One of the many interesting developments in the field of Deep Learning is the so called "Style Transfer". It describes a possibility to create a patchwork (or pastiche) from two images. While one of these images defines the the artistic style of the result picture, the other one is used for extracting the image content. The Hardware Hacking Team from TNG Technology Consulting managed to build an application using OpenCV and Tensorflow to realize such goggles. When you see the world through these glasses, your environment will be displayed in the styles of famous painters like Claude Monet or Pablo Picasso. Within this talk you will be introduced into the scientific field of Realtime Style Transfer. It will also cover and explain in detail the Deep Learning techniques used for this application.

This talk is co-presented along with Martin Fortsch

Imagine looking into a mirror, but not to see your own face, instead looking in the eyes of Barack Obama or Angela Merkel. Your facial expressions are seamlessly transferred to that other person's face, all in real time. The TNG Hardware Hacking Team has managed to create a prototype that transfers faces in real time based on Deepfakes. Neural networks detect faces within a video input, then translate and integrate them back to the video output. Through this technique it is possible to project deceptively real imitations onto other people. For this purpose, we used a Keras trained autoencoder networks and various face recognition algorithms. In this talk, the speakers will give an entertaining and vivid introduction into the world of real-time Deepfakes. In doing so, they will particularly focus on the deep learning techniques used in this application.

This talk is co-presented along with Martin Fortsch

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