Schedule
Visual Recognition and Search
EECS 6890 Topics in Information Processing (3 Credits)
Instructors: Rogerio Feris, Liangliang Cao, and Jun Wang
Home | Course Overview | Schedule | Resources | Projects | Presentations | Paper Reviews | Announcements
Important Dates
- Homework #0 due date: Jan 27 (11:59pm)
- Keep checking the deadlines for presentations, paper reviews, and project assignments
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CLASS 1 - Introduction [Rogerio] | N/A | ||
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CLASS 2 - Machine Learning Fundamentals [Jun] | This class will review basic concepts of machine learning. Check COMS 4771 Machine Learning for related topics and tutorials. | ||
| Part I: From Low-level to Semantic Visual Representations | ||||
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CLASS 3 - Low-level Feature Detection and Description [Liangliang] |
Lowe, Distinctive image features from scale-invariant keypoints, IJCV 2004 (pdf)
Check the ECCV 2012 Tutorial on Modern Features |
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| No class due to the winter storm | N/A | |||
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CLASS 4 - Mid-level Feature Coding and Pooling [Liangliang] |
Lin et al, Large-scale Image Classification: Fast Feature Extraction and SVM Training, CVPR 2011 (pdf)
Chatfield et al, The devil is in the details: an evaluation of recent feature encoding methods, BMVC 2011 (pdf) |
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CLASS 5 - Encoding Structure: Part-based Models [Rogerio] |
Felzenszwalb et al, A Discriminatively Trained, Multiscale, Deformable Part Model, CVPR 1998(pdf, Extended TPAMI 2010)
Check the ICCV 2013 Tutorial on Part-based Models for Recognition |
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CLASS 6 - Attributes and Semantic Features [Rogerio] |
Lampert et al, Attribute-Based Classification for Zero-Shot Learning of Object Categories, TPAMI 2013 (pdf)
Check the CVPR 2013 Tutorial on Attributes |
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| Part II : Tools for Large-scale Image Classification and Retrieval | ||||
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CLASS 7 - Large-scale Visual Recognition [Liangliang] |
LeCun et al, Gradient-based learning applied to document recognition, 1998 (pdf)
Krizhevsky et al, ImageNet Classification with Deep Convolutional Neural Networks, NIPS 2012 (pdf) |
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| Spring Recess (Mar 17 – Mar 21) | ||||
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CLASS 8 - Visual Similarity Based Image Search and Retrieval [Jun] |
Zhou et al, Ranking on data manifolds, NIPS 2003 (pdf)
Davis et al, Information-theoretic metric learning, ICML 2007 (pdf) |
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CLASS 9 - Smart Indexing via Learning Based Hashing [Jun] |
Weiss et al, Spectral hashing, NIPS 2008 (pdf)
Kulis and Grauman, Kernelized locality-sensitive hashing for scalable image search, ICCV 2009 (pdf) |
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CLASS 10 - Active Learning for Efficient Image Retrieval and Classification [Jun] |
Jain et al, Hashing hyperplane queries to near points with applications to large-scale active learning, NIPS 2010 (pdf)
Liu et al, Compact hyperplane hashing with bilinear functions, ICML 2012 (pdf) |
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| Part III: Case Studies | ||||
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CLASS 11 - Case Study: IBM Smart Surveillance Solution [Rogerio] |
Feris et al, Large-Scale Vehicle Detection, Indexing, and Search in Urban Surveillance Videos, TMM 2012 (pdf)
Benenson et al, Pedestrian detection at 100 frames per second, CVPR 2012 (pdf) |
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CLASS 12 - Case Study: IBM Multimedia Analysis and Retrieval System [Liangliang] |
Cao et al, Scene Aligned Pooling for Complex Video Recognition, ECCV 2012 (pdf)
Yan et al, Model-Shared Subspace Boosting for Multi-label Classification, KDD 2007 (pdf) |
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Final Project Presentations:
Flower Recognition: Feature Analysis and Fusion [Shun-Xuan Wang and Wenqian Liu] (best results to date on the Oxford Flowers Dataset) Automated Axon Segmentation Using Spatio-Temporal Independent Component Analysis [John Bowler and Mo Zhou] Identifying Animals in the Wild [Chia Kang Chao and Yen‐Cheng Chou] From ImageNet to Serengeti: Recognizing Animals in Wild Scenes [Guangnan Ye and Maja Rudolph] Recognition of Animal Skin Texture Attributes in the Wild [Amey Dharwadker and Kai Zhang] Safer Driving through Gesture Control [Kartik Darapuneni, Shuheng Gong, and Jianze Wang] |
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