Computer Vision and Deep Learning

Prof. Dr. Björn Ommer, SS 2019

Information:

Type Extent Date Room Language
Seminar 4 SWS Tuesday 14.00-16.00 INF 205 / TBA German/English: According to agreement

More Information:

  • 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 active research topics. The one chosen for the seminars of the last semester were presented in 2018 at the main conferences of computer vision.
  • Topics: Computer vision, Object classification/detection/tracking, Supervised/Unsupervised learning, Action classification, Pose estimation, Image generation/superresolution, Style transfer
  • Methods: Convolutional Neural Network (CNN), [Variational] Auto-encoder, Recursive Neural Network (RNN), Long-Short Term Model (LSTM), Generative Adversarial Network (GAN)
  • Registration required due to limited number of participants.
  • Course open for Bachelor and Master students.
  • Registration open until: TBA
  • Register by sending [name, master/bachelor, year, matrikalnumber, major, previous contact to computervision/deeplearning and possible topics of interest] at: johannes.haux@iwr.uni-heidelberg.de
  • Preliminary meeting and topic assignment: TBA
  • More information can be found in the LSF