Students are expected to do the
assigned reading, participate in class discussions, write one paper
review each week, present a paper/topic in a class and complete a final project.
A paper
presentation involves doing background research on a topic.
Note that
presentations are **one week before** the slot your presentation is scheduled. This deadline is a hard deadline. This means
you will need to read the papers, prepare experiments (optional), slides, etc.
one week before the date you are signed up for. The idea is to meet and
discuss ahead of time, so that we can iterate as needed the week leading up to
your presentation.
o
Give
a summary of the paper in your own words (very brief, 2-3 sentences)
o
What
is the main contribution of the paper?
o
What
are the primary strengths and weaknesses of the paper?
o
How
convincing are the experiments? If something specific is lacking, what
should have been tested?
o
Describe
one specific way in which the work could be extended (bonus).
o
Additional
comments, including unclear points
.
See examples
of well-written reviews.
Reviews are due by 9 PM on the night before class (Sunday). Email reviews to me, pasting the text directly into your mail (no attachments, please). Include [4738] in the subject header.
In weeks that you are
presenting, you can skip writing the reviews.
Each team (of 2 students)
will give a presentation in class covering 2 papers on a topic selected from
the course syllabus list. This presentation should
overview the papers and explain technical details, and synthesize any
underlying commonalities or highlight interesting distinctions.
The talk should be well-organized and polished, sticking to about 40 minutes (20 min.each student). Please run through it beforehand and check the time (a good rule of thumb: generally 20 minutes ~ target 20 slides total).
Include these components in the
presentation:
o
Clear
statement of the problem
o
Why
the problem is interesting, important, difficult
o
Key
technical ideas, how they work, main contributions, strengths and weaknesses
o
Evaluation,
summary of key experiments and data
o
Open
issues raised in the papers, likely extensions
Try to use applications to
motivate the work when possible, and look for visual elements (images, videos)
to put in the presentation. Check out the webpages linked on the class
webpage, and also look at authors webpages for supplementary materials.
It's ok to grab a few slides from conference talks etc. when available, but be
sure to clearly cite the source on *each* slide that is not your
own.
A project could be built
around any of the following, and should be done with a partner. Experimental evaluation should be
done on a benchmark data set ( provided in the course
page)
·
Object recognition
using bag-of-words representation and discriminative training.
·
Face detection
·
Pedestrian detection
·
Face recognition
·
Saliency
·
Action recognition
·
Image retrieval
·
Any other recognition
application we discussed in class.
You can use papers provided
as an additional reading to choose your project.
Initial project proposals will be due before the middle of the
term.
·
30%
participation (includes attendance, in-class discussions, paper reviews)
·
40%
presentations (in-class presentation)
·
30%
final project (implementaion, presentation, final
paper)