The presentations are 20 min long, including questions. So plan for 15 minutes to present and 5 min for questions. You should convey the major idea in the paper, you do not (and should not) explain every single little detail.
Some useful points:
Presentations on December 3
- Give the paper title and the authors on the first slide
- Clearly state the problem the paper tackles
- Explain the prior work on this problem and its limitation (from the prior work section in the paper
- Briefly state which limitations of the prior work the paper proposes to solve and which computational techniques will be used
- Explain the main technical details (the "meat" of the paper)
- Experimental results
- Conclusions (which issues are left to solve, future work, etc...)
- Try to use as many pictures as possible instead of text/formulas
Presentations on December 10
- Miriam: "Face Recognition with Support Vector Machinesand 3D Head Models" by
J. Huang, V. Blanz, B. Heisele
- Jun: "Co-Tracking Using Semi-Supervised Support Vector Machines" by
F. Tang, S. Brennan, Q. Zhao, H. Tao
"On the Design of Cascades of Boosted Ensembles for Face Detection"
by Charles Brubaker, J. Wu, J. Sun, M. D. Mullin and J. M. Rehg.
"Automatic Design of Cascaded classifiers" by E. Grossmann
"Object Recognition as Maching Translation: Learning a Lexicon for a Fixed Image Vocabulary"
by P. Duygulu, K. Barnard, J. Freitas, D. Forsyth
- Paulina: "FaceTracer: A Search Engine for Large Collections
of Images with Faces" by N. Kumar, P. Belhumeur, S. Nayar
Presentations at a later date:
- Maria: "Automatic Image Orientation Detection" by
A. Vailaya, H. Zhang, C. Yang, F. Liu, A. Jain
- Rachita: "Training Support Vector Machines: an Application to Face Detection" by E. Osuna, R. Freund, F. Girosi.
"Geometric Context from a Single Image" by D. Hoiem, A. Efros, M. Hebert
- Paria: "Photo and Video Quality Evaluation:
Focusing on the Subject" by Y. Luo and X. Tang
- Vida: "Learning Object Detection from a Small Number of Examples: the Importance
of Good Features" by K. Levi and Y. Weiss.
- Hossam: "Distance Metric Learning for Large Margin Nearest Neighbor
Classification" by K. Weinberger, J. Blitzer, L. Saul.