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CSE 690 Internet Vision
Organizational Meeting
Tamara BergAssistant ProfessorSUNY Stony Brook
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Course Information
Instructor: Tamara Berg Email: [email protected]: 1411 Computer ScienceWebpage: http://tamaraberg.com/
Course: Time/Location TBDOffice Hours: TBDCourse Webpage: http://tamaraberg.com/teaching/Fall_08
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About Me
First year as a professor PhD from University of California, Berkeley 2007Research Scientist at Yahoo! Research 2007-2008
TeachingFirst time teaching so I’ll be learning as we go along with all of you!
ResearchDigital Media, Computer Vision, Natural Language Processing, Web Scale projects, Integrating Words & Pictures
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About You?
• Name? • Year? • MS/PhD?• Major?• Any related background in Computer Vision,
Machine Learning, Graphics?
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Automatic Image Completion
James Hays, Alexei A. Efros. Scene Completion Using Millions of Photographs. SIGGRAPH 2007
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Face Transfer
"Face Swapping: Automatically Replacing Faces in Photographs,” D. Bitouk, N. Kumar, S. Dhillon, P. Belhumeur, S. K. Nayar, Siggraph 2008
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Photo Tourism
Noah Snavely, Steven M. Seitz, Richard Szeliski, "Photo tourism: Exploring photo collections in 3D,” SIGGRAPH 2006
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Automatic Photo Pop-Up
D. Hoiem, A.A. Efros, and M. Hebert, "Automatic Photo Pop-up", ACM SIGGRAPH 2005
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Course Organization
• Lectures• Student Paper Presentations• Course Project
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Your Responsibilities
• Attend lectures• Read assigned papers before each class and
write down at least a few questions• Participate in discussions! • Student Paper Presentations• Course project• Have fun! New and exciting area of
research with broad industrial applications.
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Lecture Topics
Visual and Multi-Media DataComputational PhotographyText Based RetrievalExemplar Based RetrievalPhoto Quality for RetrievalCombining Words & PicturesPlacesObjects, People & EventsThe role of Social Networks & Human Interaction
Including cutting edge research in: Computer Vision, Graphics, Multimedia, Information Retrieval, Machine Learning, HCI
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Student Paper Presentations
• You be the professor for a day• Prepare a presentation and lead a discussion
on a few of the assigned research papers including discussion questions, pros/cons etc
• Present a demo of the system if one is available
• Feel free to run your presentation by me in office hours beforehand
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Project
Course will be project focused
You will pick a project idea near the beginning of the semester - I can help suggest or refine project ideas in office hours.
Projects can be implementing/modifying one of the papers we discuss or original research
There will be a few status updates over the semester where you will briefly describe progress and we can provide suggestions
Projects can be completed alone or in pairs
Hopefully some of these projects can be submitted to a conference!
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Worried about the material?
• I will present a summary of useful knowledge, algorithms and related techniques near the beginning of the semester.
• This should enable you to understand most of the research papers we will read.
• If you are still worried, feel free to come see me in office hours.
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Lectures
2 classes per week, 1:20 longDiscuss 1-2 papers per class
1 class per week, 2:30 longDiscuss ~3 papers per classInformal discussions, “brown bag” seminar?
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Lecture Times?
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For next class – Data!
Please Read (links will be posted on course webpage):
80 million tiny images: a large dataset for non-parametric object and scene recognition
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Course Information
Instructor: Tamara Berg Email: [email protected]: 1411 Computer ScienceWebpage: http://tamaraberg.com/
Course Time: TBD Course Location: Will be posted on webpageOffice Hours: TBDCourse Webpage: http://tamaraberg.com/teaching/Fall_08
