PmWiki.Teaching History
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Fall '17
Fall '19
Fall '16
Fall '18
Fall '17
Computer Vision - CSCI-GA.2271-001
Fall '16
Computer Vision - CSCI-GA.2271-001
Object Recognition Tutorial
Li Fei-Fei (Stanford), Rob Fergus (NYU), Antonio Torralba (MIT)
This course reviews current methods for object category recognition, dividing them into four main areas: bag of words models; parts and structure models; discriminative methods and combined recognition and segmentation. The emphasis will be on the important general concepts rather than in depth coverage of contemporary papers. The course is accompanied by extensive Matlab demos.
It has been delivered at: ICCV 2005, CVPR 2007, ICML 2008, ICCV 2009. It was awarded the Best Short Course Prize at ICCV 2005.
Fall '13
Computational Photography - CSCI-GA.3033-012
Fall '12
Computer Vision - CSCI-GA.2271-001
Computer Vision - G22.2271
Computer Vision - G22.2271
It was awarded the Best Short Course Prize at ICCV 2005.
It was awarded the Best Short Course Prize at ICCV 2005.
Spring '12
Computer Vision - CSCI-UA.0480-001
Computer Vision - G22.2271
Computer Vision - G22.2271
Spring '11
Computational Photography - CSCI-GA.3033-002
Li Fei-Fei (Stanford), Rob Fergus (NYU), Antonio Torralba (MIT)
It was awarded the Best Short Course Prize at ICCV 2005.
Introduction to Artificial Intelligence - V22.0472 - Link
Introduction to Artificial Intelligence - V22.0472
Computational Photography - G22.3033-003 - Link
Computational Photography - G22.3033-003
Computer Vision - G22.2271 - Link
Computer Vision - G22.2271
Computational Photography - G22.3033-006 - Link
Computational Photography - G22.3033-006
Classroom Teaching
Spring '10
Computational Photography - G22.3033-001 - Link
Fall '09
Teaching
Spring '10
Computational Photography - G22.3033-001
Fall '09
Spring '09
Spring '09
Fall '08
Fall '08
Spring '08
Spring '08
Object Recognition Tutorial
This course reviews current methods for object category recognition, dividing them into four main areas: bag of words models; parts and structure models; discriminative methods and combined recognition and segmentation. The emphasis will be on the important general concepts rather than in depth coverage of contemporary papers. The course is accompanied by extensive Matlab demos.
It has been delivered at: ICCV 2005, CVPR 2007, ICML 2008, ICCV 2009.
Object Recognition Tutorial
This course reviews current methods for object category recognition, dividing them into four main areas: bag of words models; parts and structure models; discriminative methods and combined recognition and segmentation. The emphasis will be on the important general concepts rather than in depth coverage of contemporary papers. The course is accompanied by extensive Matlab demos.
It has been delivered at: ICCV 2005, CVPR 2007, ICML 2008, ICCV 2009.
Teaching
Object Recognition Tutorial
This course reviews current methods for object category recognition, dividing them into four main areas: bag of words models; parts and structure models; discriminative methods and combined recognition and segmentation. The emphasis will be on the important general concepts rather than in depth coverage of contemporary papers. The course is accompanied by extensive Matlab demos.
It has been delivered at: ICCV 2005, CVPR 2007, ICML 2008, ICCV 2009.
Classroom Teaching
Teaching
Computational Photography - G22.3033-003 - Link
Computational Photography - G22.3033-003 - Link
Fall '08
Computer Vision - G22.2271 - Link
Spring '08
Computational Photography - G22.3033-006 - Link
Spring '10
Introduction to Artificial Intelligence - V22.0472 - Link
Spring '09
Computational Photography - G22.3033-003 - Link
Spring '10
Computational Photography - G22.3033-001 - Link