Computer Vision Misc Reading Group
Wednesdays, 3:00 - 4:30, EDSH 200

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2012 Schedule

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Date Presenter Description
1/25/2012 Pyry Learning to Predict the Perceived Visual Quality of Photos
Ou Wu, NLPR (Institute of Automation), Weiming Hu (Institute of Automation), Jun Gao
ICCV 2011

Content-Based Photo Quality Assessment
Wei Luo, Xiaogang Wang, Xiaoou Tang
ICCV 2011

Assessing the aesthetic quality of photographs using generic image descriptors
Luca Marchesotti (XRCE), Florent Perronnin (XRCE), Diane Larlus (XRCE), Gabriela Csurka (XRCE)
ICCV 2011
2/1/2012 Abhinav G. Im2Text: Describing Images Using 1 Million Captioned Photographs
Vicente Ordonez, Girish Kulkarni, Tamara Berg
NIPS 2011

Learning person-object interactions for action recognition in still images
Vincent Delaitre, Josef Sivic, Ivan Laptev
NIPS 2011
2/8/2012 Ed Evaluation of Image Features Using a Photorealistic Virtual World
B. Kaneva, A. Torralba and W. T. Freeman
ICCV 2011

Local Intensity Order Pattern for Feature Description
Z. Wang, B. Fan and F. Wu
ICCV 2011

CENTRIST : A Visual Descriptor for Scene Categorization
J. Wu and J. M. Rehg
TPAMI 2011
3/14/2012 Varun Articulated Part-based Model for Joint Object Detection and Pose Estimation
Min Sun, Silvio Savarese
ICCV 2011

N-best maximal decoders for part models
Dennis Park, Deva Ramanan
ICCV 2011

Strong Supervision From Weak Annotation: Interactive Training of Deformable Part Models
Steven Branson Pietro Perona, Serge Belongie
ICCV 2011
3/21/2012 Ali TBA
3/28/2012 Feng Y. HaCohen, E. Shechtman, D. B. Goldman, and D. Lischinski,
Non-Rigid Dense Correspondence with Applications for Image Enhancement,

H. Jiang, S. X. Yu, and D. R. Martin,
Linear Scale and Rotation Invariant Matching,
PAMI 2011
4/4/2012 Dong Localizing Parts of Faces Using a Consensus of Exemplars
Peter N. Belhumeur, David W. Jacobs, David J. Kriegman, Neeraj Kumar
CVPR 2011

Latent Structured Models for Human Pose Estimation
Catalin Ionescu, Fuxin Li, Cristian Sminchisescu
ICCV 2011
4/11/2012 Munoz A Pylon Model for Semantic Segmentation
V. Lempitsky, A. Vedaldi, A. Zisserman
NIPS 2011

Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers
C. Farabet, C. Couprie, L. Najman, Y. LeCun

Decision Tree Fields
S. Nowozin, C. Rother, S. Bagon, T. Sharp, B. Yao, and P. Kohli
ICCV 2011
4/18/2012 Scott Accidental pinhole and pinspeck cameras: revealing the scene outside the picture
Antonio Torralba, Bill Freeman
CVPR 2012

Recognizing Scene Viewpoint using Panoramic Place Representation
Jianxiong Xiao, Krista A. Ehinger, Aude Oliva, Antonio Torralba
CVPR 2012

Unsupervised co-segmentation through region matching
Jose C. Rubio, Joan Serrat, Antonio Lopez, Nikos Paragios
CVPR 2012
4/25/2012 -- Special VASC Seminar: Jon Barron
5/2/2012 Mark D. Image Saliency: From Intrinsic to Extrinsic Context
Wang, M., J. Konrad, P. Ishwar, K. Jing, and H. Rowley
CVPR 2011

Learning a Category Independent Object Detection Cascade
Rahtu, E., J. Kannala, and M. Blaschko
ICCV 2011

What Is an Object?
Alexe, B., T. Deselaers, and V. Ferrari
CVPR 2010
5/9/2012 Xuehan Integrating Multiple-Study Multiple-Subject fMRI Datasets Using Canonical Correlation Analysis
I. Rustandi, M.A. Just, T.M. Mitchell.
MICCAI 2009 Workshop: Statistical modeling and detection issues in intra- and inter-subject functional MRI data analysis 2009

Multi-label Output Codes using Canonical Correlation Analysis
Yi Zhang and Jeff Schneider
5/16/2012 Maturana Teaching 3D Geometry to Deformable Part Models
B. Pepik, M. Stark, P. Gehler, B. Schiele
CVPR 2012

Learning 3D object templates by hierarchical quantization of geometry and appearance spaces
W. Hu
CVPR 2012

From Contours to 3D Object Detection and Pose Estimation
N. Payet and S. Todorovic
ICCV 2011
5/23/2012 Stambler Detection-based Object Labeling in 3D Scenes
Lai, Kevin, Liefeng Bo, and Xiaofeng Ren
ICRA 2012

SURFing the Point Clouds: Selective 3D Spatial Pyramids for Category-level Object Recognition
C. Redondo-Cabrera, R. J. Lopez-Sastre, J. Acevedo-Rodriguez and S. Maldonado-Bason
CVPR 2012
5/30/2012 Fouhey Recovering Free Space of Indoor Scenes from a Single Image
V. Hedau, D. Hoiem, D. Forsyth
CVPR 2012

Bayesian Geometric Modeling of Indoor Scenes
L. Del Pero, J. Bowdish, D. Fried, B. Kermgard, E. Hartley, K. Barnard
CVPR 2012

Efficient Structured Prediction for 3D Indoor Scene Understanding
A. Schwing, H. Tamir, M. Pollefeys, R. Urtasun
CVPR 2012
6/6/2012 Gunhee On Multiple Foreground Cosegmentation
G. Kim, E. Xing
CVPR 2012

Web Image Prediction Using Multivariate Point Processes
G. Kim, F-F Li, E. Xing
KDD 2012
6/13/2012 -- Guest speaker: Joao Fayad
3D Deformable models for Non-Rigid Structure from Motion
7/11/2012 Kitani First-person vision
7/18/2012 Alvaro E. Zeng et al.,
Clustering Genes using Heterogeneous Data Sources
International Journal of Knowledge Discovery in Bioinformatics 2010

A. Strehl and J. Ghosh,
Cluster Ensembles - A Knowledge Reuse Framework for Combining Multiple Partitions
JMLR 2002

Z. Lu and I. S. Dhillon,
Clustering with Multiple Graphs,
ICDM 2009
7/25/2012 Yuandong Learning from Crowds in the Presence of Schools of Thought
Yuandong Tian, Jun Zhu
KDD 2012
8/1/2012 Tomas A Simple Prior-free Method for Non-Rigid Structure-from-Motion Factorization
Yuchao Dai, Hongdong Li, Mingyi He
CVPR 2012

General Trajectory Prior for Non-Rigid Reconstruction
Jack Valmadre, Simon Lucey
CVPR 2012
8/8/2012 Henry Figure-ground segmentation by transferring window masks
Daniel Kuettel, Matthieu Guillaumin, and Vittorio Ferrari
CVPR 2012
8/15/2012 Leonid No Bias Left Behind: Covariate Shift Adaptation for Discriminative 3D Pose Estimation
Makoto Yamada, Leonid Sigal, Michalis Raptis
ECCV 2012
8/22/2012 Ashiqur KhudaBukhsh Leveraging User Comments for Aesthetic Aware Image Search Reranking
Jose San Pedro, Tom Yeh, and Nuria Oliver
WWW 2012
8/29/2012 Carl SIGGRAPH overview
9/5/2012 Zhou Yu Collective Generation of Natural Image Descriptions
P. Kuznetsova, V. Ordonez, A. Berg, T. Berg, Y Choi
ACL 2012
9/12/2012 -- VASC Seminar
9/19/2012 Jun-Yan Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning
Jun-Yan Zhu, Jiajun Wu, Yichen Wei, Eric Chang and Zhuowen Tu
CVPR 2012

Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering
Yan Xu, Jun-Yan Zhu, Eric Chang and Zhuowen Tu
CVPR 2012

Contexts-Constrained Multiple Instance Learning for Histopathology Image Segmentation
Yan Xu, Jianwen Zhang, Eric Chang, Maode Lai, and Zhuowen Tu
9/26/2012 Natasha Reconstructing the World's Museums
J. Xiao and Y. Furukawa
ECCV 2012

Interactive Images: Cuboid Proxies for Smart Image Manipulation
Y. Zheng et al.
10/3/2012 Olivier Discriminative Decorrelation for Clustering and Classification" European Conference on Computer Vision
B. Hariharan, J. Malik, D. Ramanan
ECCV 2012
10/24/2012 Ricardo Shape Sharing for Object Segmentation
Jaechul Kim and Kristen Grauman
ECCV 2012
12/5/2012 Abhinav S. NIPS 2012:
Analyzing 3D Objects in Cluttered Images
3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model
Shifting Weights: Adapting Object Detectors from Image to Video
Localizing 3D cuboids in single-view images
Learning about Canonical Views from Internet Image Collections
Searching for objects driven by context
A Generative Model for Parts-based Object Segmentation
12/12/2012 Yair Has My Algorithm Succeeded? An Evaluator for Human Pose Estimators
Jammalamadaka, N., Zisserman, A., Eichner, M., Ferrari, V., & Jawahar, C. V.
ECCV 2012

Object Detection Using Strongly-Supervised Deformable Part Models
Azizpour, H., & Laptev, I.
ECCV 2012

Learning About Canonical Views from Internet Image Collections
Elad Mezuman and Yair Weiss
NIPS 2012

Dog Breed Classification Using Part Localization
Liu, Jiongxin, Angjoo Kanazawa, David Jacobs, and Peter Belhumeur
ECCV 2012

Meetings in Previous Years

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1. How is the presenters' order generated?
The presenters' order is generated from the presenters' list in a FIFO manner.

2. Who is responsible if I can not present at the scheduled time?

3. What should I do if I can not present at the scheduled time?
First, let the organizer know your situation, as early as possible. Second, contact other presenters on the list and see if they are willing to swap with you.

4. What happens if a new event takes place and we have to change the schedule?
To minimize disturbance, the conflited slot will be moved to the rear of the list after confirmed with the originally scheduled presenter, while all the other schedules remain unchanged.

5. I have a question not listed here...

This file is located at: /afs/cs/project/vmr/www/misc_read/