| 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 |
| (Back to Top) | ||
| 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 | TBA |
| 6/5/2013 | Gunhee | TBA |
| 6/12/2013 | Tomas | TBA |
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.
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