Advanced Topics in Computer Vision (048921) – Tentative list of topics

Winter 2011

Tentative list of topics

Below you may find a tentative list of topics. You may suggest to me (via email) other topics which are of interest to you and do not appear on the list below (please include a list of relevant papers).
You should wait for my formal confirmation before starting to work on a topic.

Direct link to many of the papers below can be found here


1a) Databases in computer vision – Ran Margolin

The PASCAL Visual Object Classes (VOC) Challenge ,
M. Everingham, L. Van Gool, C.K.I. Williams, J. Winn, A. Zisserman.
IJCV 2010

Unbiased Look at Dataset Bias ,
A. Torralba, A. Efros.
CVPR 2011

1b) Pascal grand challenge

Image Classification Using Super-Vector Coding of Local Image Descriptors ,
X. Zhou, K. Yu, T. Zhang, T.S. Huang. 
ECCV 2010.

Object Detection with Discriminatively Trained Part-Based Models ,
P.F. Felzenszwalb, R.B. Girshick, D. McAllester, D. Ramanan. 
PAMI 2010.

2) Human pose recognition – Sariel Ben-Arye

Real-time Human Pose Recognition in Parts from Single Depth Images
Jamie Shotton , Andrew Fitzgibbon, Mat Cook, Andrew Blake
CVPR 2011

Recovering 3D human pose from monocular images
Agarwal, A. and Triggs, B.
PAMI 2006

3a) Action recognition – Shay Perera

Recognizing Human Actions by Attributes
Jingen Liu
CVPR 2011

Human Action Recognition by Learning Bases of Action Attributes and Parts 

Bangpeng Yao, Xiaoye Jiang, Aditya Khosla, Andy Lai Lin, Leonidas J. Guibas, Li Fei-Fei
ICCV 2011

3b) Action recognition – Avner Atias

Learning Spatiotemporal Graphs of Human Activities 
William Brendel, Sinisa Todorovic
ICCV 2011

Cross-View Action Recognition via View Knowledge Transfer 
Jingen Liu
CVPR 2011

Learning hierarchical spatio-temporal features for action recognition with independent subspace analysis. 
Quoc Le, Will Zou , Serena Yeung, Andrew Ng
CVPR 2011

A “String of Feature Graphs” Model for Recognition of Complex Activities in Natural Videos
Utkarsh Gaur, Yingying Zhu, Bi Song, Amit Roy-Chowdhury
ICCV 2011

4) View selection – Marlene Schehada

Discovering Favorite Views of Popular Places with Iconoid Shift 
Tobias Weyand, Bastian Leibe
ICCV 2011

Viewpoint-Aware Object Detection and Pose Estimation 
Daniel Glasner, Meirav Galun, Sharon Alpert, Ronen Basri, Gregory Shakhnarovich
ICCV 2011

Selecting Canonical Views for View-based 3D Object Recognition.
T. Denton, M. Demirci, J. Abrahamson, A. Shokoufandeh, and S. Dickinson.
ICPR, 2004


5) Scene reconstructionAnton Jigalin

Discrete-Continuous Optimization for Large-scale Structure from Motion
David Crandall, Andrew Owens, Noah Snavely, Daniel Huttenlocher,
CVPR 2011

Scene Reconstruction and Visualization from Internet Photo Collections: A Survey
Snavely, N.
IPSJ Transactions on Computer Vision and Applications

6) Image registration – Raz Nossek

Smoothly Varying Affine Stitching 
Wen Yan Lin, Siying Liu, Yasuyuki Matsushita, Tian Tsong Ng
CVPR 2011

Constructing Image Panoramas using Dual-Homography Warping
J. Gao, S. J. Kim, M. S. Brown, 
CVPR 2011

Mathematical utilities useful for computer vision

7) Efficient search methods – Itamar Friedman

PatchMatch: a randomized correspondence algorithm for structural image editing
Barnes, C. and Shechtman, E. and Finkelstein, A. and Goldman, D.B.

Coherency Sensitive Hashing
Simon Korman, Shai Avidan
CVPR 2011

8a) Grouping and segmentation

Harmony Potentials for Joint Classification and Segmentation,
J.M. Gonfaus, X. Boix, J. Van de Weijer, A. D. Bagdanov, J. Serrat, and J. Gonzàlez,
in CVPR 2010.

Object Detection and Segmentation from Joint Embedding of Parts and Pixels
Michael Maire, Stella X. Yu, Pietro Perona
ICCV 2011

8b) Subspace clustering – Amir Adler

A Closed Form Solution to Robust Subspace Estimation and Clustering 
Paolo Favaro, RenéVidal, Avinash Ravichandran
CVPR 2011

Robust Subspace Segmentation by Low Rank Representation
Guangcan Liu, Zhouchen Lin,Yong Yu
ICML 2010

Sparse Subspace Clustering
Ehsan Elhamifar, René Vidal
CVPR 2009

9) Compressed sensing

An Introduction To Compressive Sampling ,
E.J. Candes, M.B. Wakin.
IEEE Signal Processing Magazine, March 2008.

Learning compressed sensing ,
Y. Weiss, H.S. Chang, W.T. Freeman.
Snowbird Learning Workshop, 2007.

Stable signal recovery from incomplete and inaccurate measurements ,
E. Candesy, J. Romberg, T. Tao.
Comm. Pure Appl. Math., August 2006.

Single-pixel imaging via compressive sampling ,
M. Duarte, M. Davenport, D. Takhar, J. Laska, T. Sun, K. Kelly, R. Baraniuk.
IEEE Signal Processing Magazine, March 2008.

Internal Statistics of a Single Natural Image.
M. Zontak  and   M. Irani, 
CVPR 2011

10) Low-rank methods – Boris Kimelman

RASL: Robust Alignment by Sparse and Low-rank Decomposition for Linearly Correlated Images 
Yigang Peng, Arvind Balasubramanian, John Wright, Ma Yi
CVPR 2011

11) Denoising – Royi Avital

A review of image denoising algorithms, with a new one.
A Buades, B Coll, JM Morel –
SIAM Journal on Multiscale Modeling and Simulation, 2006

Image denoising by sparse 3-D transform-domain collaborative filtering
K Dabov, A Foi, V Katkovnik, K. Egiazarian.
IEEE Trans Image Processing, 2007

A Tour of Modern Image Processing.
P. Milanfar.
Invited feature article in review IEEE Signal Processing Magazine, 2010.


12) Computer vision and aesthetics – Dmitry Rudoy

High Level Describable Attributes for Predicting Aesthetics and Interestingness,
Sagnik Dhar, Vicente Ordonez, Tamara L. Berg,
CVPR 2011

Exploring aesthetic principles of spatial composition through stock photography
Gardner, J.S. and Fowlkes, C. and Nothelfer, C. and Palmer, S.E.
Journal of Vision, 2008

Optimizing Photo Composition,
L. Liu, R. Chen, L. Wolf and D. Cohen-Or,

13) Single Image Super-Resolution – Tomer Faktor

Super-Resolution from a Single Image,
D. Glasner, S. Bagon, and M. Irani,
ICCV 2009.

Image Super-Resolution via Sparse Representation,
J.Yang, J. Wright, T. Huang, and Y. Ma,
IEEE Trans Image Processing, 2010.

On Single Image Scale-Up using Sparse-Representations,
R. Zeyde, M. Elad, and M. Protter,
Curves & Surfaces, 2010.

Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity,
G.Yu, G. Sapiro, and S. Mallat,
submitted, 2010 (available at arxiv).

14) Large scale image retrieval – Dima Sezganov

Smooth Object retrieval using Bag of Boundaries
R. Arandjelovic, A. Zisserman

ICCV 2011.

Image retrieval with geometry preserving visual phrases
Y. Zhang, Z. Jia, T. Chen
CVPR 2011

Spatial bag-of-features
Y. Cao, C. Wang, Z. Li, L. Zhang, L. Zhang
CVPR 2010


15) Video compression – Yehuda Dar

A Scheme for Attentional Video Compression
R. Gupta, S. Chaundhury

PAMI 2011.

3D models coding and morphing for efficient video compression
F. Galpin, R. Balter, L. Morin, K. Deguchi
CVPR 2004

16) Deblurring – Idan Ram

Handling Outliers in Non-blind Image Deconvolution
S. Cho, J. Wang, S. Lee

ICCV 2011.

Blind Motion Deblurring Using Image Statistics.
A. Levin.
NIPS 2006

Image and depth from a conventional camera with a coded aperture
A. Levin, R. Fergus, F. Durand, and W. T. Freeman.

Understanding and evaluating blind deconvolution algorithms.
A. Levin, Y. Weiss, F. Durand, W. T. Freeman

CVPR 2009.

Removing camera shake from a single photograph.
R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman.


17) Shape reconstruction of transparent surfaces – Coral Moreno

Reconstructing the Surface of Inhomogeneous Transparent Scenes by Scatter-Trace Photography
N.J.W. Morris, K.N. Kutulakos

ICCV 2007.

Fluorescent Immersion Range Scanning
M.B. Hullin, M. Fuchs, I. Ihrke, H. Seidel, H.P.A. Lensch