Computer Vision Misc Reading Group
Wednesdays, 3:00 - 4:30, EDSH 200
2013 Schedule
Date
Presenter
Description
1/9/2013
Gupta
Memorability of Image Regions
Khosla et al.
NIPS 2012
Understanding and Predicting Importance in Images
Berg et al.
CVPR 2012
Detecting Visual Text
Dodge et al.
NAACL 2012
1/16/2013
--
Guest: Ruiqi Guo
1/23/2013
Varun
Domain Adaptation of Conditional Probability Models via Feature Subsetting
Sandeepkumar Satpal and Sunita Sarawagi
ECML 2007
Appearance Sharing for Collective Human Pose Estimation
Marcin Eichner, Vittorio Ferrari
ACCV 2012
Weakly Supervised Learning of Object Segmentations from Web Scale Video
Hartmann et al.
ECCV 2012 Workshop on Web-scale vision
1/30/2013
Feng
Action Recognition with Exemplar Based
Bangpeng Yao Li Fei-Fei
ECCV 2012
Max-Margin Structured Output Regression for Spatio-Temporal Action Localization
Du Tran and Junsong Yuan
NIPS 2012
2/6/2013
Dong
Temporal Factorization Vs. Spatial Factorization
Lihi Zelnik-Manor and Michal Irani
ECCV04
Sparse Subspace Clustering: Algorithm, Theory, and Applications
Ehsan Elhamifar and Rene Vidal
Arxiv 2012
Improved Subspace Clustering via Exploitation of Spatial Constraints
Duc-Son Pham
CVPR12
2/13/2013
Scott
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
Milos Radovanov, Alexandros Nanopoulos and Mirjana Ivanovi
Journal of Machine Learning Research 2010
The Myth of Goats: How many people have fingerprints that are hard to match?
Austin Hicklin, Craig Watson and Brad Ulery
NIST Tech Report 2005
Discriminative Decorrelation for Clustering and Classification
Bharath Hariharan, Jitendra Malik and Deva Ramanan
ECCV 2012
2/20/2013
Ed
Multiple View Object Cosegmentation using Appearance and Stereo Cues
A. Kowdle, S. Sinha and R. Szeliski
ECCV 2012
Object Co-detection
S.Y. Bao, Y. Xiang and S. Savarese
ECCV 2012
2/27/2013
Yong Jae
Recognizing Proxemics in Personal Photos
Yi Yang, Simon Baker, Anitha Kannan, Deva Ramanan
CVPR 2012
Automatic Discovery of Groups of Objects for Scene Understanding
Congcong Li, Devi Parikh, Tsuhan Chen
CVPR 2012
3/6/2013
Jacob
Detecting activities of daily living in first-person camera views
Hamed Pirsiavash, Deva Ramanan
CVPR 2012
Building high-level features using large scale unsupervised learning
Le et al.
ICML 2012
3/13/2013
Hanbyul
Laplacian Meshes for Monocular 3D Shape Recovery
J. O. M. Ostlund, A. Varol, T. D. Ngo and P. Fua
ECCV 2012
Linear Local Models for Monocular Reconstruction of Deformable Surfaces
M. Salzmann and P. Fua
PAMI 2011
4/17/2013
Aravindh
ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning
Quoc V. Le, Alexandre Karpenko, Jiquan Ngiam and Andrew Y. Ng
NIPS 2011
Building high-level features using large scale unsupervised learning
Q.V. Le, M.A. Ranzato, R. Monga, M. Devin, K. Chen, G.S. Corrado, J. Dean, A.Y. Ng
ICML, 2012
4/24/2013
Zhuo
Modeling Actions through State Changes
Alireza Fathi and James M. Rehg
CVPR 2013
Novelty Detection from an Ego-Centric Perspective
Omid Aghazadeh, Josephine Sullivan and Stefan Carlsson
CVPR 2011
5/1/2013
Xinlei
Learning Collections of Part Models for Object Recognition
Ian Endres, Kevin J. Shih, Johnston Jiaa, Derek Hoiem
CVPR 2013
Harvesting Mid-level Visual Concepts from Large-scale Internet Images
Quannan Li, Jiajun Wu, and Zhuowen Tu
CVPR 2013
Part Discovery from Partial Correspondence
Subhransu Maji, Gregory Shakhnarovich
CVPR 2013
5/8/2013
Kris
Determinantal Point Processes for Machine Learning
Alex Kulesza and Ben Taskar
Foundations and Trends in Machine Learning 2012
5/15/2013
Ishan
Fast, Accurate Detection of 100,000 Object Classes on a Single Machine
Thomas Dean, Jay Yagnik, Mark Ruzon, Mark Segal, Jonathon Shlens, Sudheendra Vijayanarasimhan
CVPR 2013
Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots
Chao-Yeh Chen, Kristen Grauman
CVPR 2013
Fast Object Detection with Entropy-Driven Evaluation
Raphael Sznitman , Carlos Becker, Francois Fleuret, Pascal Fua
CVPR 2013
5/29/2013
Maturana
Comparative evaluation of binary features
J. Heinly, E. Dunn, J. M. Frahm
ECCV 2012
From bits to images: inversion of local binary descriptors
E. d'Angelo, L. Jacques, A. Alahi and P. Vandergheynst
ICPR 2012
FREAK: Fast Retina Keypoint
A. Alahi, R. Ortiz, P. Vandergheynst
CVPR 2012
LUCID: Locally Uniform Comparison Image Descriptor
A. Ziegler, E. Christiansen, D. Kriegman, S. Belongie
NIPS 2012
Boosting Binary Keypoint Descriptors
T. Trzcinski, M. Christoudias, P. Fua and V. Lepetit
CVPR 2013
6/5/2013
Gunhee
Unsupervised Joint Object Discovery and Segmentation in Internet Images
Michael Rubinstein, Armand Joulin, Johannes Kopf, Ce Liu
CVPR 2013
Large-Scale Video Summarization Using Web-Image Priors
Aditya Khosla, Raffay Hamid, Chih-Jen Lin, Neel Sundaresan
CVPR 2013
6/12/2013
Tomas
Dense Variational Reconstruction of Non-Rigid Surfaces from Monocular Video
Ravi Garg, Anastasios Roussos, Lourdes Agapito
CVPR 2013
Dense Object Reconstruction with Semantic Priors
Yingze Bao, Manmohan Chandraker, Yuanqing Lin, Silvio Savarese
CVPR 2013
Learning a Manifold as an Atlas
Nikolaos Pitelis, Chris Russell, Lourdes Agapito
CVPR 2013
What's in a Name? First Names as Facial Attributes
Huizhong Chen, Andrew Gallagher, Bernd Girod
CVPR 2013
7/10/2013
TBA
CVPR 2013 Recap
7/17/2013
Leon
S. Mathe and C. Sminchisescu. "Dynamic Eye Movement Datasets and Learned
Saliency Models for Visual Action Recognition." In European Conference on
Computer Vision, October 2012.
E. Vig, Dorr, M., and Cox, D., "Space-Variant Descriptor Sampling for
Action Recognition Based on Saliency and Eye Movements", in LNCS 7578,
Proceedings of the European Conference on Computer Vision, Firenze, Italy:
Springer, 2012, p. 84-97.
7/24/2013
Xinlei
Analogy-preserving Semantic Embedding for Visual Object Categorization
Sung Ju Hwang, Kristen Grauman and Fei Sha
A Sentence is Worth a Thousand Pixels
S. Fidler, A. Sharma and R. Urtasun
Generating Natural-Language Video Descriptions Using Text-Mined Knowledge
Niveda Krishnamoorthy, Girish Malkarnenkar, Raymond J. Mooney, Kate Saenko, Sergio Guadarrama
Grounding Action Descriptions in Videos
M. Regneri, M. Rohrbach, D. Wetzel, S. Thater, B. Schiele and M. Pinkal
7/31/2013
Natasha
User-Assisted Image Compositing for Photographic Lighting
Ivaylo Boyadzhiev, Sylvain Paris, Kavita Bala
Optimizing Color Consistency in Photo Collections
Yoav HaCohen, Eli Schechtman, Dan Goldman, Dani Lischinski
Global Illumination with Radiance Regression Functions
Peiran Ren, Jiaping Wang, Minmin Gong, Stephen Lin, Xin Tong, Baining Guo
Rectangling Panoramic Images via Warping
Kaiming He, Huiwen Chang, Jian Sun
8/7/2013
Yair
Decoding Children's Social Behavior
J Rehg, G Abowd, A Rozga, MRM Clements, L Presti, S Sclaroff, I Essa
CVPR 2013
Behavior Imaging: Using Computer Vision to Study Autism.
JM Rehg
MVA2011
Temporal causality for the analysis of visual events
K Prabhakar, S Oh, P Wang, GD Abowd, JM Rehg
CVPR 2010
Categorizing turn-taking interactions
K Prabhakar, JM Rehg
ECCV 2012
8/14/2013
Kate
Event Retrieval in Large Video Collections with Circulant Temporal Encoding
Jerome Revaud, Matthijs Douze, Cordelia Schmid, Herve Jegou
CVPR 2013
Discriminative Segment Annotation in Weakly Labeled Video
Kevin Tang, Rahul Sukthankar, Jay Yagnik, Li Fei-Fei
CVPR 2013
Story-Driven Summarization for Egocentric Video
Zheng Lu, Kristen Grauman
CVPR 2013
8/21/2013
Nick
Finding Things: Image Parsing with Regions and Per-Exemplar Detectors.
Joseph Tighe and Svetlana Lazebnik, CVPR 2013
Object Recognition by Sequential Figure-Ground Ranking.
J. Carreira, F. Li and C. Sminchisescu, IJCV 2012
IEEE transactions on pattern analysis and machine intelligence, 2005.
T. Basha, Y. Moses, and N. Kiryati, .Multi-view Scene Flow Estimation: A View Centered Variational Approach,.
IJCV, 2013.
S. Hadfield and R. Bowden, .Kinecting the dots: Particle based scene flow from depth sensors,.
ICCV, 2011.
9/4/2013
David
Bringing Semantics Into Focus Using Visual Abstraction. C.L. Zitnick, D.
Parikh. CVPR 2013
Learning the Visual Interpretation of Sentences. C.L. Zitnick, D. Parikh. L. Vanderwende.
ICCV 2013
9/16/2013
Feng
Computational High-Speed Video
9/25/2013
Dong
HON4D: Histogram of Oriented 4D Normals for Activity Recognition from
Depth Sequences, CVPR 2013
Spatio-Temporal Depth Cuboid Similarity Feature for Activity
Recognition Using Depth Camera, CVPR 2013.
Recognizing object manipulation activities using depth and visual
cues, Journal of Visual Communication and Image Representation, 2013
10/2/2013
Jacob
"A data-driven approach for event prediction."
Jenny Yuen, Antonio Torralba. European Conference on Computer Vision (ECCV), 2010.
10/9/2013
Zhou
"Fine-Grained Crowdsourcing for Fine-Grained Recognition"
Jia Deng, Jonathan Krause, Li Fei-Fei CVPR 2013
10/16/2013
Maheen
"Understanding Indoor Scenes using 3D Geometric Phrases
CVPR, 2013 W. Choi, Y. Chao, C. Pantofaru and S. Savarese"
10/23/2013
Aravindh
Mishra, Ajay K., Yiannis Aloimonos, Loong Fah Cheong, and Ashraf Kassim.
"Active visual segmentation." Pattern Analysis and Machine Intelligence,
IEEE Transactions on 34, no. 4 (2012): 639-653.
11/6/2013
Ishan
Shufflets: shared mid-level parts for fast object detection, I. Kokkinos
ICCV 2013
SIFTpack: a compact representation for efficient SIFT matching, A.
Gilinsky and L. Manor
ICCV 2013
11/13/2013
Chia-Yin
E.Steger and K.Kutulakos. A Theory of Refractive and Specular 3D Shape by Light-Path Triangulation. IJCV 2008
G. Wetzstein, D. Roodnick, W. Heidrich, and R. Raskar. Refractive Shape from Light Field Distortion. ICCV 2011
V. Chari and P. Sturm. A Theory of Refractive Photo-Light-Path Triangulation. CVPR 2013
(Back to Top)
11/20/2013
Jian Wang
Lensless imaging by compressive sensing, Gang Huang,
Hong Jiang, Kim Matthews and Paul Wilford, 2013 (Archive)
Lensless Imaging with a Controllable Aperture, Assaf Zomet, Shree K. Nayar, CVPR 2006
Single pixel imaging via compressive sampling, Marco F. Duarte, et.al.,
IEEE Signal Processing Magazine, 2008
Meetings in Previous Years
Related Links
FAQ
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?
Youself.
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...
Ask.
This file is located at: /afs/cs/project/vmr/www/misc_read/