| 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 |
| 8/28/2013 | Hanbyul |
S. Vedula, S. Baker, P. Rander, R. Collins, and T. Kanade, .Three-dimensional scene flow.,. 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 |
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| 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 |
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.
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