Computer Vision and Deep Learning

Prof. Dr. Björn Ommer, WS 2020/21

Information:

Type Extent Date Room Language
Seminar 4 SWS Thursday, 11:00 - 13:00 Online English

More Information:

  • Topics: Computer vision, Object classification/detection/tracking, Supervised/Unsupervised learning, Action classification, Pose estimation, Image & video synthesis/superresolution, Style transfer, Interpretability of deep models, ...
  • Description: Each student will choose a paper among a set of proposed papers. The student needs to understand the paper, present it in front of the class and write a short report about it.
  • Hot topics: all papers are chosen from current research topics and were published very recently in the major conferences/journals of the field.
  • Methods: Convolutional Neural Networks (CNN), [Variational] Auto-encoders, Generative Adversarial Network (GAN), Recurrent Neural Networks (RNN), Invertible Models, ...
  • Registration required due to limited number of participants. We strongly recommend to register as soon as possible.
  • Register by sending [name, master/bachelor, the semester you will be in, matriculation number, major, previous experience with computer vision/deep learning and possible topics of interest] at: matthias.wright@iwr.uni-heidelberg.de. The email should have the subject: Computer Vision Seminar Registration
  • Preliminary meeting and topic assignment: TBA
  • More information can be found in the LSF