I will oppose:
47. J. Winn and N. Jojic. LOCUS: Learning Object Classes with Unsupervised Segmentation, Proc. IEEE Intl. Conf. on Computer Vision (ICCV), Beijing 2005.

I'd like to demo either
24. Xiaofeng Ren and Jitendra Malik, Learning a Classification Model for Segmentation. in ICCV '03
or
65. D. D. Lee and H. S. Seung. Learning the parts of objects by non-negative matrix factorization. Nature 401, 788-791 (1999)
but neither was picked by anyone to be presented.
Should I give a brief introduction before I demo?
For 65, is the code available even though there is no link to it and I couldn't find it in the author's webpage?

Edited by author 01-25-2006 09:55 PM
I'd like to oppose

22. Weiss, Y. Segmentation using eigenvectors: a unifying view.

23. Andrew Y. Ng, Michael I. Jordan, Yair Weiss, On Spectral Clustering: Analysis and an algorithm

I'll oppose Dave Thompson on the isomap/lle papers.

I can demo the following (depending on whether anyone wants to present it)

1)#8 T. F. Cootes, G. J. Edwards, C. J. Taylor, Active Appearance Models, PAMI 2001
and/or
2)#37 Ramanan, Forsyth, Zisserman. Strike a Pose: Tracking People by Finding Stylized Poses, CVPR 2005

We need to start finding opponents and demoers for the papers.
In particular, we need an opponent (and perhaps a demo?) for the upcoming Torralba papers.

Looks like Dave will do the Ullman papers and I will give an overview of bag-of-words models. So, we would need an opponent for that.

Edited by author 01-23-2006 01:19 PM
I can present and demo the remaining dimensionality reduction papers:
 63) J. B. Tenenbaum, V. De Silva, and J. C. Langford
 64) Sam Roweis & Lawrence Saul

I'll oppose David Lowe's SIFT paper.

I can present:
Tamara L. Berg, Alexander C. Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik Learned-Miller, David A. Forsyth. Names and Faces.

I am sad to see that #15-16 didn't get picked by anyone.
If there are people without papers (or not enough papers), these are nice (and relatively simple).
I will conver 12-14 myself briefly.

I can also present the following if there is a need to present another one.
David G. Lowe, Object Recognition from Local Scale-Invariant Features, ICCV 1999

I would like to demo:
Jianbo Shi; Malik, J. Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, Aug. 2000, vol.22, (no.8):888-905.

And oppose:
Belongie, Malik, and Puzicha. Shape Matching and Object Recognition Using Shape Contexts (2002)
and
A Berg, T Berg, J Malik, Shape Matching and Object Recognition using Low Distortion Correspondences, CVPR 2005

Maloha: #60 already taken by Stephan.
Regarding #61, would you be able to also do a tutorial on MRF models? Following Geman&Geman or something?

SungWon: you definitely don't have to do 3 papers. Either 1 big one or 2 small ones is fine. I say, you can safely drop #65.

Seth: if you do Adelson & pentland, why not also do "World of painted polyhedra"? They are quite related.

OK, how are we doing on papers? Do we have enough yet?

Dhiraj,
    #30 was already claimed by Ellie along with #29. A list of who claimed what on this discussion board is available at http://www.cs.cmu.edu/~efros/courses/AP06/...papers_assigned.htm
Although this list is not official yet because it hasn't been approved by Alyosha.

    -Dave

I would like to present on these topics


59 Marshall F Tappen, William T Freeman, Edward H Adelson, Recovering Intrinsic Images from a Single Image. NIPS 2002. (there is also a longer version that was published in the September 2005 issue of IEEE Transactions on Pattern Analysis and Machine Intelligence)
 

60 Hoiem, Efros, Hebert, Geometric Context from a Single Image, ICCV 2005 (code available)
 

61 Ashutosh Saxena, Sung Chung, and Andrew Y. Ng. Learning Depth from Single Monocular Images. NIPS 2005.

I'm interested in presenting:
30. Viola, Jones, Robust Real-time Object Detection (2001)

I’d like to present:
26. D. Comaniciu, P. Meer. Mean Shift: A Robust Approach toward Feature Space Analysis
40. T. F. Cootes, G. J. Edwards, C. J. Taylor, Active Appearance Models
65. D. D. Lee and H. S. Seung. Learning the parts of objects by non-negative matrix factorization

Btw, how many topics can or must a student present? Is there any limitation of the number of presentations?