AGNI Theses

 

In this thesis / project, you will have the opportunity to further develop an Artificial Intelligenceagent capable of performing complex purposeful actions in Minecraft or Doom environments. 

If you would like to know more about this thesis / project opportunity, please watch this video and contact:

Dr. Andrew Melnik <andrew.melnik@uni-bielefeld.de> 

  Figure: animation of faces from old family photos using Deep Learning approaches

 

Virtual try on of clothes with deep learning and image segmentation using just a 2d image. To create a shopping environment close to reality, virtual try-on technology has attracted a lot of interests recently by delivering product information similar to that obtained from direct product examination. It allows users to experience themselves wearing different clothes without efforts of changing them physically. 

https://arxiv.org/pdf/1807.07688.pdf

https://nanonets.com/blog/semantic-image-segmentation-2020

If you would like to know more about this thesis / project opportunity, please contact: Dr. Andrew Melnik <andrew.melnik(at)uni-bielefeld.de>

Vision-Based robot control typically requires a large amount of manual tuning and feature selection (edge, color, SIFT features, etc.). Modern (GPU-driven) computing power and more robust numerical methods, nowadays allow for training of deep neural networks that extract suitable features for a given task automatically and that are able to learn control tasks in an end-to-end fashion, i.e.