16-824 Learning Based Methods in Vision (Spring 2015)

Course Schedule for Spring 2015

Date	Presenter	Topic	Papers
01/12/2015	Abhinav Gupta	Introduction	-
01/14/2015	Abhinav Gupta	Theories of Vision	J. Mundy. Object Recognition in the Geometric Era: a Retrospective, Springer Berlin Heidelberg, 2006. 3-28
01/19/2015	Martin Luther King Holiday (No Class)
01/21/2015	Abhinav Gupta	Theories of Vision (Cont.)	-
01/26/2015	Abhinav Gupta	Introduction to Data	A. Halevy, P. Norvig, and F. Pereira. The Unreasonable Effectiveness of Data, IEEE Intelligent Systems, 24 8--12, 2009. A. Torralba, and A. Efros. Unbiased Look at Dataset Bias, CVPR, 2011.
01/28/2015	Abhinav Gupta	Introduction to Data	-
02/02/2015	Abhinav Gupta	Introduction to Learning	S. Andrews, I. Tsochantaridis and T. Hofmann. Support vector machines for multiple-instance learning, NIPS, 2002. A. Criminisi, J. Shotton and E. Konukoglu. Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning, Foundations and Trends in Computer Graphics and Computer Vision. NOW Publishers. Vol.7: No 2-3, pp 81-227. 2012.
02/04/2015	Abhinav Gupta	Overview of Papers	-
02/09/2015	Abhinav Gupta	Introduction to Deep Learning	G. Hinton and R. Salakhutdinov. Reducing the dimensionality of data with neural networks, Science 313.5786 (2006): 504-507. L. Bottou. Stochastic gradient descent tricks, Neural Networks: Tricks of the Trade. Springer Berlin Heidelberg, 2012. 421-436.
02/11/2015	Abhinav Gupta	Low Level Features	D. Lowe. Distinctive image features from scale-invariant keypoints, IJCV 60.2 (2004): 91-110. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection, CVPR, 2005. A. Oliva and A. Torralba. Modeling the shape of the scene: A holistic representation of the spatial envelope, IJCV 42.3 (2001): 145-175.
02/16/2015	Xinlei Chen	Introduction to Caffe Toolbox	Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, T. Darrell Caffe: Convolutional Architecture for Fast Feature Embedding, arXiv preprint arXiv:1408.5093 (2014). F. Iandola, M. Moskewicz, S. Karayev, R. Girshick, T. Darrell, K. Keutzer DenseNet: Implementing Efficient ConvNet Descriptor Pyramids, arXiv preprint arXiv:1404.1869 (2014).
02/19/2015	Elissa Aminoff	Uncovering Visual Cortex	-
02/23/2015	Abhinav Gupta	Image Classification	A. Krizhevsky, I. Sutskever and G. Hinton. Imagenet classification with deep convolutional neural networks, NIPS, 2012. K. Simonyan and A. Zisserman. Very Deep Convolutional Networks for Large-Scale Image Recognition, arXiv preprint arXiv:1409.1556 (2014). M. Zeiler and R. Fergus. Visualizing and Understanding Convolutional Networks, ECCV, 2014.
02/25/2015	Xinwu Yang and Hanbyul Joo	Image Segmentation	P. Arbelaez, M. Maire, C. Fowlkes and J. Malik. Contour detection and hierarchical image segmentation, TPAMI 33, no. 5 (2011): 898-916. J. Carreira and C. Sminchisescu. Constrained parametric min-cuts for automatic object segmentation, CVPR, 2010. J. Long, E. Shelhamer and T. Darrell. Fully convolutional networks for semantic segmentation, arXiv preprint arXiv:1411.4038 (2014).
03/02/2015	Xinlei Chen	Recitation	-
03/04/2015	Xiaolong Wang and Rohit Girdhar	Object Detection	P. Felzenszwalb, R. Girshick, D. McAllester and D. Ramanan. Object detection with discriminatively trained part-based models, TPAMI 32, no. 9 (2010): 1627-1645. R. Girshick, J. Donahue, T. Darrell, J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation, arXiv preprint arXiv:1311.2524 (2013). C. Szegedy, S. Reed, D. Erhan, D. Anguelov. Scalable, High-Quality Object Detection, arXiv preprint arXiv:1412.1441 (2014).
03/09/2015	Spring Break (No Class)
03/11/2015	Spring Break (No Class)
03/16/2015	Namhoon Lee and Shreyansh Daftry	Object Detection with 3D Models	M. Aubry, D. Maturana, A. Efros, B. Russell, J. Sivic. Seeing 3D chairs: exemplar part-based 2D-3D alignment using a large dataset of CAD models, CVPR, 2014. J. Lim, A. Khosla and A. Torralba. FPM: Fine pose Parts-based Model with 3D CAD models, ECCV, 2014. A. Dosovitskiy, J. Springenberg, T. Brox. Learning to Generate Chairs with Convolutional Neural Networks, arXiv preprint arXiv:1411.5928 (2014).
03/18/2015	Tejas Mathai and Ganesh	Attributes and Zero-Shot Recognition	A. Farhadi, I. Endres, D. Hoiem and D. Forsyth. Describing Objects by their Attributes, CVPR, 2009. N. Kumar, A. Berg, P. Belhumer and S. Nayar. Attribute and Simile Classifiers for Face Verification, ICCV, 2009. D. Parikh and K. Grauman. Relative attributes, ICCV, 2011.
03/23/2015	Wei-Chiu Ma and Chao Liu	Mid-level Patches	L. Bourdev and J. Malik. Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations, ICCV, 2009. S. Singh, A. Gupta and A. Efros. Unsupervised discovery of mid-level discriminative patches, ECCV, 2012. Y. Li, L. Liu, C. Shen, A. Hengel. Mid-level Deep Pattern Mining, arXiv preprint arXiv:1411.6382 (2014).
03/25/2015	David Fouhey	3D Scene Understanding	D. Lee, A. Gupta, M. Hebert and T. Kanade. Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces, NIPS, 2010. D. Eigen, C. Puhrsch, R. Fergus. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network, arXiv preprint arXiv:1406.2283 (2014). X. Wang, D. Fouhey, A. Gupta. Designing Deep Networks for Surface Normal Estimation, arXiv preprint arXiv:1411.4958 (2014).
03/30/2015	Esha Uboweja and Minh Vo	Action Recognition/Videos	A. Jain, A. Gupta, M. Rodriguez, L. Davis. Representing videos using mid-level discriminative patches, CVPR, 2013. A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, F. Li. Large-scale Video Classification with Convolutional Neural Networks, CVPR, 2014. K. Simonyan, A. Zisserman. Two-Stream Convolutional Networks for Action Recognition in Videos, arXiv preprint arXiv:1406.2199 (2014).
04/01/2015	Sahil Shah and Harrison Billmers	Context-based Reasoning	B. Yao and F. Li. Modeling Mutual Context of Object and Human Pose in Human-Object Interaction Activities, CVPR, 2010. Z. Tu Auto-context and Its Application to High-level Vision Tasks, CVPR, 2008. D. Hoiem, A.A. Efros, and M. Hebert, Putting Objects in Perspective, IJCV 2008.
04/06/2015	Yiying Li and Calvin Murdock	Unsupervised Learning	B. Russell, A. Efros, J. Sivic, B. Freeman, A. Zisserman. Using Multiple Segmentations to Discover Objects and their Extent in Image Collections, CVPR, 2006. Y. Lee and K. Grauman. Object-Graphs for Context-Aware Visual Category Discovery, CVPR, 2010. Q. Le, M. Ranzato, R. Monga, M. Devin, K. Chen, G. Corrado, J. Dean and A. Ng. Building high-level features using large scale unsupervised learning, ICML, 2012.
04/08/2015	Leonid Sigal	Human Pose Estimation	Y. Yang and D. Ramanan. Articulated Human Detection with Flexible Mixtures-of-Parts, CVPR, 2011.
04/13/2015	Ankit Laddha and Gunnar Sigurdsson	Semi-supervised Learning	R. Fergus, Y. Weiss and A. Torralba. Semi-supervised Learning in Gigantic Image Collections, NIPS, 2009. A. Shrivastava, S. Singh and A. Gupta. Constrained Semi-Supervised Learning Using Attributes and Comparative Attributes, ECCV, 2012. S. Reed, H. Lee, D. Anguelov, C. Szegedy, D. Erhan, A. Rabinovich. Training Deep Neural Networks on Noisy Labels with Bootstrapping, arXiv preprint arXiv:1412.6596 (2014).
04/15/2015	Lerrel Pinto and Yimeng Zhang	Weakly-supervised Learning	X. Chen, A. Shrivastava and A. Gupta. Enriching Visual Knowledge Bases via Object Discovery and Segmentation, CVPR, 2014. H. Song, R. Girshick, S. Jegelka, J. Mairal, Z. Harchaoui and T. Darrell. On learning to localize objects with minimal supervision, ICML, 2014. C. Wang, W. Ren, K. Huang and T. Tan. Weakly Supervised Object Localization with Latent Category Learning, ECCV, 2014.
04/20/2015	Meng Song and Venkatesh	Learning from the Web	L. Li and F. Li. Optimol: automatic online picture collection via incremental model learning, IJCV, 88.2 (2010): 147-168. X. Chen, A. Shrivastava and A. Gupta. NEIL: Extracting Visual Knowledge from Web Data, ICCV, 2013. S. Divvala, A. Farhadi and C. Guestrin. Learning Everything about Anything: Webly-Supervised Visual Concept Learning, CVPR, 2014.
04/22/2015	ICCV Deadline (No Class)
04/27/2015	Karanhaar Singh and Zehua Huang	Text and Images	G. Kulkarni, V. Premraj, S. Dhar, S. Li, Y. Choi, A. Berg and T. Berg. Baby Talk: Understanding and Generating Image Descriptions, CVPR, 2011. V. Ordonez, G. Kulkarni and T. Berg. Im2Text: Describing Images Using 1 Million Captioned Photographs, NIPS, 2011. X. Chen, C. Zitnick. Learning a Recurrent Visual Representation for Image Caption Generation, arXiv preprint arXiv:1411.5654 (2014).
04/29/2015	All	Final Project Presentations	-

Learning Based Methods in Vision

Course Schedule for Spring 2015

Instructor Info

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The Robotics Institute