CS 598 - High-Level Recognition inComputer Vision |
Spring 2007by Fei-Fei Li |
Course home | Outline and lecture notes | Course project |
Date |
Lecture (click for notes) |
Assignments |
Presenter |
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Wed, Feb 7 |
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Wed, Feb 14 |
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Fei-Fei |
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1. Single Object Recognition | 1. Lowe ICCV 1999; Lowe IJCV 2004 | Brendan | |
Wed, Feb 21 |
1. Pictorial structure for objects |
Bryan |
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2. Object categ.: the constellation model |
Fei-Fei |
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Wed, Feb 28 |
1. AdaBoosting for face recognition |
Melissa |
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2. Sharing features: Joint Boosting |
Melissa |
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Wed, Mar 7 |
1. Implicit Shape Models for objects |
Christine |
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2. Hierarchical probabilistic model |
Dmitry |
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Wed, Mar 14 |
1. Convolutional NN |
Matt |
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2. Biologically inspired visual recognition model |
Andy |
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Wed, Mar 14 |
Mid-term report of your course project due IN CLASS! |
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Wed, Mar 28 | 1. ImageParsing: hybrid model |
Aleksey |
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2. ObjCut: segmentation and recognition |
Bryan |
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Wed, Apr 4 |
1. Patch-based segmentation and recognition |
Tiffany |
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2. Epitomes and Jigsaws |
Zhe |
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Wed, Apr 1 | 1. SVM: pyramid kernel |
Tiffany |
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2. Tree structure based segmentation and recognition |
Brendan |
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Wed, Apr 18 |
1. CRF for segmentation |
Richard |
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2. Layout consistent random field for occluded objects |
Corey |
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Wed, Apr 25 |
1. Latent Topic Models for objects |
Richard |
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2. Nonparametric latent topic model |
Corey |
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Wed, May 2 |
course project presentation |
peer reviewed |
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Tue, May 15 |
Dean's date |
Final project report due |
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