16-721 is a graduate seminar devoted to recent research on computer vision. We will be reading an eclectic mix of vision papers on topics such as perception, object and scene recognition, segmentation, tracking, as well as "best papers of all time".
We will meet on Mondays and Wednesdays from 10:30am-11:50am in NSH 3002. The first meeting will be on Monday January 16th, and the final meeting will be on Wednesday May 3, 2006.
Instructor: Alexei (Alyosha) Efros, Assistant Professor, 4207 Newell-Simon Hall.
Office Hours: Monday 12:-12:30 p.m.
Friday 2:30-3:30 p.m.
TA: David Bradley, 2216 Newell-Simon Hall.
Office Hours: Tuesday 1:00-2:00 p.m. or by appointment.
Feel free to send email to efros (at) cs or dbradley (at) cs with any questions.
Check out this list of data sources for some ideas on where to get images to work with.
Time
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Monday (A)
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Wednesday (A)
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Monday (B)
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Wednesday (B)
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12:10
- 12:30
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N/A
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Zickler
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N/A
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Vallespi
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12:30
- 12:50
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Thompson & Dunlop
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Batra & Kim
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12:50
- 1:10
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Ramnath
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Chan & Barnum
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1:10
- 1:30
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Djugash
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1:30
- 1:50
|
Melchior
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A list of suggested papers to present is available here.
For some journal-length papers, shorter conference versions have been posted. Feel free to read either paper.
The discussion board for signing up for papers is now available here
Sign up for at least 2 papers, demo 1 and oppose 1.
If you want to change your presentation date, please arrange a swap with another student and notify the instructor at least two weeks in advance.
|
date |
Presenter |
paper title |
author(s) |
discussion |
slides |
|
Jan. 16 |
Alyosha Efros |
Introduction,
Vision: Measurement vs. Perception Administrative stuff,
overview of the course, datasets |
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Jan. 18 |
Alyosha Efros |
Overview lecture on the physiology of vision Suggested reading: The Plenoptic Function and the Elements
of Early Vision (1991) |
Adelson & Bergen |
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Jan. 23 |
Alyosha Efros Dave Thompson |
Overview lecture on theories of Visual Perception Vision
is getting easier every day (1995) What's up
in top-down processing? (1991) Pictorial art and vision (1991) |
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Part I:
Low-level Vision (images as texture) |
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Jan. 25 |
Peter Barnum Heather Dunlop |
Presenting: The
Earth Mover's Distance as a Metric for Image Retrieval. (conference version) Optional Presenting: Learning
to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture
Cues (conference version) |
Rubner , Tomasi, & Guibas Rubner, Puzicha, Tomasi, & Buhmann Martin, Fowlkes, Malik |
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Jan. 30 |
Jonathan Huang |
Statistics
of Natural Image Categories Optional Optional |
Torralba & Oliva Torralba, & Oliva Oliva & Torralba |
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Feb. 1 |
Alyosha Efros |
Presenting an overview
of bag-of-words appraoches:
Optional: When is scene recognition
just texture recognition?
Optional: Visual categorization with bags of keypoints
Optional: Object Categorization by
Learned Universal Visual Dictionary |
Renninger, L.W. & Malik, J G. Csurka, C. Bray, C. Dance, and L. Fan Winn, A. Criminisi and T. Minka |
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|
Feb. 6 |
David
Bradley |
Presenting: Object
Recognition with Informative Features and Linear Classification Optional |
Ullman, S., Vidal-Naquet, M. , and Sali, E Michel Vidal-Naquet,
Shimon Ullman |
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Feb. 8 |
Tomasz Malisiewicz (P) Alyosha Effros (O) |
A Bayesian
hierarchical model for learning natural scene categories. |
Fei-Fei and P. Perona Josef Sivic, Bryan Russell, Alexei A. Efros, Andrew
Zisserman, Bill Freeman |
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Part II: Mid-level Vision (Image Segmentation) |
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Feb. 13-15 |
Carlos Vallespi (P) Joseph Djugash (D) Gunhee Kim (O) |
Jianbo Shi; Malik, J. Weiss, Y. |
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Feb. 20 |
Mohit Gupta (P) |
Interactive
Graph Cuts for Optimal Boundary & Region Segmentation of Objects in ND
Images Optional: Lazy
Snapping Optional: Video Object Cut and Paste (cool SIGGRAPH video) |
Boykov & Jolly Yin Li, Jian Sun, Chi-Keung Tang, Heung-Yeung Shum Yin Li, Jian Sun, Heung-Yeung Shum |
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Feb. 22 |
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Project Proposals |
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Feb. 27 |
Derek Hoiem |
Derek Hoiem, Alexei Efros, Martial Hebert |
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Mar. 1 |
Tomasz Malisiewicz (P) |
Tu and Zhu |
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Part
III: 2D Recognition |
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Mar. 6 (A) |
Nicolas Chan
(P) Tomasz Malisiewicz (O) Pete Barnum (D) |
H. Schneiderman and T.
Kanade Viola, Jones |
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Mar. 8 (A) |
Pete Barnum (P) |
Dalal, Triggs |
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Mar.
13 |
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Spring Break |
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Mar.
15 |
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Spring Break |
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Mar. 20 (B) |
David Lee (P) Heather Dunlop (D) David Thompson (O) |
David G. Lowe |
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Mar. 22 (B) |
Stephan Zickler (P) |
Real-time Object
Detection for Smart Vehicles Optional: Automatic Target Recognition by Matching Oriented Edge Pixels |
Gavrila & Philomin Olson & Huttenlocher |
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Mar. 27 (A) |
Gunhee Kim (P) Joseph Djugash (O) ? (D) |
Shape Matching
and Object Recognition Using Shape Contexts Shape Matching and Object Recognition using Low Distortion Correspondences |
Belongie, Malik, and Puzicha A Berg, T Berg, J Malik |
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Mar. 29 (A) |
Dhruv Batra (P) Krishnan Ramnath (D) |
*NEW: paper
changed to a more readable version*
Active Appearance Models Optional: Active Appearance Models Revisited Optional: Manipulating
Facial Appearance Through Shape and Color |
T. F. Cootes, G. J. Edwards, C. J. Taylor Matthews & Baker Rowland & Perret Blanz & Vetter |
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Recognition with Segmentation |
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Apr. 3 (B) |
Joseph Djugash (P) Heather Dunlop (O) |
Eran Borenstein, Shimon Ullman Eran Borenstein, Shimon Ullman E. Borenstein, |
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Apr. 5 (B) |
Dhruv Batra (P) |
B Leibe, |
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Apr. 10 (A) |
Nik Melchior (P) David Lee (O) Stephan Zickler (D) |
LOCUS: Learning
Object Classes with Unsupervised Segmentation |
J. Winn and N. Jojic |
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Apr. 12 (A) |
David Lee (P) Carlos Vallespi (O) Gunhee Kim (D) |
Context-based
vision system for place and object recognition Optional:
Contextual
Models for Object Detection using Boosted Random Fields |
A. Torralba, K. P. Murphy, W. T. Freeman and M. A. Rubin |
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Machine Translation
Approaches |
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Apr. 17 (B) |
Heather Dunlop (P) |
Object
recognition as machine translation: Learning a lexicon for a fixed image
vocabulary |
Pinar Duygulu, Kobus Barnard, Nando de Freitas, and
David Forsyth Kobus Barnard, Pinar Duygulu, Nando de Freitas, David Forsyth, David Blei, and Michael I. Jordan |
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Apr. 19 (B) |
Krishnan Ramnath (P) Nicholas Chan (D) Nicolas Chan (O) |
Tamara L. Berg, Alexander C. Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik Learned-Miller, David A. Forsyth |
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Intrinsic
Images |
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Friday Apr.
21 (A) NSH
4201 |
Mohit Gupta (P) Mohit Gupta (D) Malola Prasath (P) David Lee (D) Nik Melchoir (O) |
Deriving
intrinsic images from image sequences |
Yair Weiss Marshall F Tappen, William T Freeman, Edward H Adelson |
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Apr. 26 (A) |
Stephan Zickler (P) |
Adelson & Pentland |
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Manifold
Learning |
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May 1 |
Dave Thompson (P) Jonathan Huang (O) Nik
Melchoir (D) |
A global
geometric framework for nonlinear dimensionality reduction Nonlinear
dimensionality reduction by locally linear embedding |
J. B. Tenenbaum, V. De
Silva, and J. C. Langford Sam Roweis & Lawrence Saul |
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May 3 |
Ramnath & Gupta Batra & Kim Huang & Malisiewicz Melchior & Lee Stefan Zickler |
Project Presentations – Part I |
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May 8 |
Chan & Barnum Djugash Thompson & Dunlop Carlos Vallespi |
Project Presentations – Part II |
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Vision Science:
Photons to Phenomenology by Stephen E. Palmer
Computer Vision: A Modern
Approach, Forsyth and Ponce
Introductory
Techniques for 3-D Computer Vision Trucco and Verri
An Invitation to 3D Vision:
From Images to Geometric Models, Y. Ma, S. Soatto, J. Kosecka, S. Sastry
Multiple View Geometry in
Computer Vision by Hartley & Zisserman
The Geometry of
Multiple Images by Faugeras, Luong, and Papadopoulo
Neural
Networks for Pattern Recognition, Bishop.
Most recently updated on January. 27, 2006 by David Bradley
Site design courtesy of Serge Belongie.