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HU Credits:
2
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Computer Sciences
Semester:
2nd Semester
Teaching Languages:
English and Hebrew
Campus:
E. Safra
Course/Module Coordinator:
Prof Amnon Shashua
Coordinator Office Hours:
Coordinate in advance
Teaching Staff:
Prof Michael Werman
Prof Shmuel Peleg
Ms. Inbar Huberman
Course/Module description:
A seminar/reading group focused on recent work in computer vision. We
will cover papers from recent and upcoming conferences related to
computer vision (CVPR, ICCV, ECCV, NIPS, SIGGRAPH). The seminar is
open to everyone. We especially encourage first year graduate students
who may be considering research in computer vision or related areas to participate.
Logistics
Time: Tuesdays from 1:30pm-2:30pm
Location: CSE 403
Organizers: Neeraj Kumar (neeraj @ cs washington edu) and Bryan
Russell (bcr @ cs washington edu)
Class mailing list: cse590v @ cs washington edu (subscribe here)
Seminar
Each week we will cover a recent topic in computer vision by reading
and discussing one or more relevant papers. A person will lead the
discussion by presenting the chosen paper(s) for the week. We
encourage all attendees to read the paper(s) beforehand and to
actively participate in the discussion.
Advanced topics in computer vision and image understanding. The
students will present current research of their own and discuss papers
from the recent conferences. There will also be a number of talks from
visiting scholars.
Course/Module aims:
See learning outcomes
Learning outcomes - On successful completion of this module, students should be able to:
Students will learn how to disseminate academic papers in the field and be exposed to the latest academic results in computer vision. The seminar will prepare students to start performing research in computer vision.
Attendance requirements(%):
100
Teaching arrangement and method of instruction:
Seminar
Course/Module Content:
will be given at the course
Required Reading:
NA
Additional Reading Material:
papers would be given in advance
Course/Module evaluation:
End of year written/oral examination 0 %
Presentation 100 %
Participation in Tutorials 0 %
Project work 0 %
Assignments 0 %
Reports 0 %
Research project 0 %
Quizzes 0 %
Other 0 %
Additional information:
NA
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