PD Federico Tombari
Recent Trends in 3D Computer Vision and Deep Learning
, Prof. Nassir Navab
, Iro Laina
, Helisa Dhamo
Course number: Module IN4826
Advanced Seminar Course Module IN8901
Master Seminar Module IN2107
Seminar Module IN0014
- To express your interest for the seminar, you can send us your motivation letter/email (including relevant courses that you have taken) at rt3dcvdl-w18|[at]|googlegroups.com, until 05.07.2018.
- Preliminary meeting: Thursday, 28.06.2018 at 13:15. Location: 03.13.010
- The Seminar Course concerns recent advances in the field of 3D Computer Vision and Deep Learning. The Seminar will propose a list of recent scientific articles related to the main current research topics in the field, such as 3D keypoint detection and description, point cloud matching and registration, 3D object recognition and classification, SLAM, 3D reconstruction, 3D object pose estimation and tracking, depth prediction, 3D scene understanding.
In this Master Seminar, each student is asked to select one paper from a list. In order to successfully complete the seminar, participants have to fulfill these requirements:
- Presentation: The selected paper is presented to the other participants (20 minutes presentation 10 minutes questions). Use the CAMP templates for PowerPoint camp-tum-jhu-slides.zip, or Latex: CAMP-latex-template.
- Written Report: A document of maximum 8 pages is written and submitted one week after the presentation. Please download and use the llncs2e.zip Latex template.
- Attendance: Participants have to participate actively in all seminar sessions.
The students are required to attend each seminar presentation which will be held during this course. Each presentation is followed by a discussion and everyone is encouraged to actively participate. The report must include all references used and must be written completely in your own words
. Copy and paste will not be tolerated. Both report and presentation have to be done in English
List of Topics and Material
The schedule for the paper presentations will be announced here during the semester. Each student is required to attend all presentations.