Siyu Tang: Catalogue data in Autumn Semester 2021

Name Prof. Dr. Siyu Tang
FieldComputer Vision
Address
Professur für Computer Vision
ETH Zürich, CNB G 104
Universitätstrasse 6
8092 Zürich
SWITZERLAND
E-mailsiyu.tang@inf.ethz.ch
URLhttps://vlg.inf.ethz.ch
DepartmentComputer Science
RelationshipAssistant Professor (Tenure Track)

NumberTitleECTSHoursLecturers
252-5701-00LAdvanced Topics in Computer Graphics and Vision Information Restricted registration - show details
Number of participants limited to 24.

The deadline for deregistering expires at the end of the third week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
2 credits2SM. Pollefeys, O. Sorkine Hornung, S. Tang
AbstractThis seminar covers advanced topics in computer graphics, such as modeling, rendering, animation, real-time graphics, physical simulation, and computational photography. Each time the course is offered, a collection of research papers is selected and each student presents one paper to the class and leads a discussion about the paper and related topics.
Learning objectiveThe goal is to get an in-depth understanding of actual problems and research topics in the field of computer graphics as well as improve presentations and critical analysis skills.
ContentThis seminar covers advanced topics in computer graphics,
including both seminal research papers as well as the latest
research results. Each time the course is offered, a collection of
research papers are selected covering topics such as modeling,
rendering, animation, real-time graphics, physical simulation, and
computational photography. Each student presents one paper to the
class and leads a discussion about the paper and related topics.
All students read the papers and participate in the discussion.
Lecture notesno script
LiteratureIndividual research papers are selected each term. See http://graphics.ethz.ch/ for the current list.
263-5902-00LComputer Vision Information 8 credits3V + 1U + 3AM. Pollefeys, S. Tang, F. Yu
AbstractThe goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.
Learning objectiveThe objectives of this course are:
1. To introduce the fundamental problems of computer vision.
2. To introduce the main concepts and techniques used to solve those.
3. To enable participants to implement solutions for reasonably complex problems.
4. To enable participants to make sense of the computer vision literature.
ContentCamera models and calibration, invariant features, Multiple-view geometry, Model fitting, Stereo Matching, Segmentation, 2D Shape matching, Shape from Silhouettes, Optical flow, Structure from motion, Tracking, Object recognition, Object category recognition
Prerequisites / NoticeIt is recommended that students have taken the Visual Computing lecture or a similar course introducing basic image processing concepts before taking this course.
264-5800-18LDoctoral Seminar in Visual Computing (HS21) Information 1 credit1SM. Pollefeys, O. Sorkine Hornung, S. Tang
AbstractIn 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 caThis graduate seminar provides doctoral students in computer science a chance to read and discuss current research papers.
Learning objectiveIn 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.
ContentCurrent research at the IVC will be presented and discussed.
Prerequisites / NoticeThis course requires solid knowledge in the area of Computer Graphics and Computer Vision as well as state-of-the-art research.