Computer Graphics Laboratory ETH Zurich


PhD Seminar - SS 17

Course Topics and Objectives

In this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges can be discussed, and also to practice scientific presentations.

Course Setup

The seminar takes place in the spring and autumn semester.


This course requires solid knowledge in the area of Computer Graphics and Computer Vision as well as state-of-the-art research.

Performance assessment

Ungraded semester performance. Presence is mandatory (75% of the seminar talks, i.e., 9 out of 12) to pass the seminar. Presence is formally controlled. Every participant has to present his/her research once a year.


Number 264-5800-06L
Organizers M. Gross, O. Sorkine, M. Pollefeys
Coordinator Vinicius Da Costa De Azevedo
Location CAB G 51, Friday, 12-13 (starting at 12:15)
ECTS Credits 1


Date Name Topic
24/02 Dr. Tobias Günter Opacity optimization and inertial particles
03/03 Dr. Cengiz Öztireli Point Processes in Computer Graphics
10/03 No seminar
17/03 Dr. Roi Poranne Optimal mappings in geometry processing
24/03 Dr. Vinicius C. Azevedo Grids, Particles, Boundaries and Incompressibility in Fluid Animation
31/03 Dr. Moritz Bäecher Computational Design and Manufacturing at Disney Research
07/04 Dr. Torsten Sattler Mapping and Localization
14/04 Easter Break
21/04 Easter Break
28/04 Dr. Paulo Gotardo Inverse Rendering for 3D Capture and Effects
05/05 PhD Students Presentation Hantao Zhao: Re-designing Public Spaces in the Era of AI and VR
Riccardo Roveri: Point Sampling with Adaptive Density and Correlations
12/05 PhD Students Presentation Loic Ciccone: Authoring Motion Cycles
Ian Cherabier: Towards large scale semantic 3D reconstruction
19/05 PhD Students Presentation Katarina Tothova: Cortical Surface Reconstruction
26/05 No Seminar
02/06 PhD Students Presentation Katja Wolff: Packable Springs
Ancona Marco: Visualising and understanding predictions with neural networks