Category: teaching

SAILORS 2016: AI will change the world. Who will change AI?

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By , July 22, 2016

2016_sailors_projects_lambertoIn the past two weeks I have been involved as computer vision project mentor in the Stanford Artificial Intelligence Laboratory’s OutReach Summer program (SAILORS). SAILORS is a summer camp for high school girls and it is intended to increase diversity in the field of AI. SAILORS aims to teach technically rigorous AI concepts in the context of societal impact.

Check out SAILORS blog to know more about the program. SAILORS was also recently featured in Wired.

CVPR’16 Tutorial on Image Tag Assignment, Refinement and Retrieval

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By , June 27, 2016

Cees Snoek and Lamberto Ballan - CVPR 2016We gave a tutorial on “Image Tag Assignment, Refinement and Retrieval” at CVPR 2016, based on our survey. The focus is on challenges and solutions for content-based image retrieval in the context of online image sharing. We present a unified review on three problems: tag assignment, refinement, and tag-based image retrieval.

The slides are available on this page.

ACM MM’15 Tutorial on Image Tag Assignment, Refinement and Retrieval

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By , October 29, 2015

12183790_10153302893771359_4417098406233994063_oWe gave a tutorial on “Image Tag Assignment, Refinement and Retrieval” at ACM MM 2015, based on our recent survey. Our tutorial focuses on challenges and solutions for content-based image retrieval in the context of online image sharing and tagging. We present a unified review on three closely linked problems: tag assignment, tag refinement, and tag-based image retrieval. We introduce a taxonomy to structure the growing literature, understand the ingredients of the main works, and recognize their merits and limitations.

We provided also an hands-on session with the main methods, software and datasets. All data, code and slides are online at: http://www.micc.unifi.it/tagsurvey

SAILORS 2015: Tutorial on Nearest Neighbors for Image Classification

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By , August 7, 2015

Lamberto Ballan - Stanford SAILORS 2015 - kNN tutorialI have just given a tutorial on kNN at the Stanford Artificial Intelligence Laboratory’s Outreach Summer program (SAILORS). SAILORS is designed to expose high school students in underrepresented populations to the field of Artificial Intelligence.

The slides are available on this page and the Matlab code is also available for download. This is an updated version of the code used in class and should work also on Octave.

ICPR 2014 Tutorial: Hands on Advanced Bag-of-Words Models for Visual Recognition

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By , July 30, 2014

Lamberto Ballan and Lorenzo Seidenari at ICPR 2014

Lorenzo Seidenari and I gave the tutorial “Hands on Advanced Bag-of-Words Models for Visual Recognition” at the ICPR 2014 conference (August 24, Stockholm, Sweden).

All materials – i.e. slides, Matlab code, images and features – and more details can still be found on this webpage.

Lab Bag-of-Words

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By , November 14, 2013

University of Florence
Course on Multimedia Databases – 2013/14 (Prof. A. Del Bimbo)
Instructors: Lamberto Ballan and Lorenzo Seidenari

Goal

The goal of this laboratory is to get basic practical experience with image classification. We will implement a system based on bag-of-visual-words image representation and will apply it to the classification of four image classes: airplanes, cars, faces, and motorbikes.

We will follow the three steps:

  1. Load pre-computed image features, construct visual dictionary, quantize features
  2. Represent images by histograms of quantized features
  3. Classify images with Nearest Neighbor / SVM classifiers

Getting started

  • Download excercises-description.pdf
  • Download lab-bow.zip (type the password given in class to uncompress the file) including the Matlab code
  • Download 4_ObjectCategories.zip including images and precomputed SIFT features; uncompress this file in lab-bow/img
  • Download 15_ObjectCategories.zip including images and precomputed SIFT features; uncompress this file in lab-bow/img
  • Start Matlab in the directory  lab-bow/matlab and run exercises.m

DBMM 2013 Contest

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By , October 30, 2013

DBMM 2012 Contest

MICC laboratories, Florence, 31th October 2013 (10.15-13.15). Course on Multimedia Databases (DBMM) – laboratory lecture.

  • Goal: logo recognition in web images.
  • Dataset/testset: find 4 different logos vs 110 images.
  • Evaluation metrics: recognition performances will be evaluated in terms of mean Average Precision (mAP).

Instructors: Lamberto Ballan, Lorenzo Seidenari.

Download Software & Dataset Go to document (* based on VLFeat library by A. Vedaldi)

Final results (ranking): http://goo.gl/o5DCG5

ICIAP 2013 Tutorial: Hands on Advanced Bag-of-Words Models for Visual Recognition

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By , September 7, 2013

ICIAP2013Lorenzo Seidenari and I will give a tutorial named “Hands on Advanced Bag-of-Words Models for Visual Recognition” at the forthcoming ICIAP 2013 conference (September 9, Naples, Italy). All materials (slides, Matlab code, etc.) and more details can be found on this webpage.

MICC Reading Group on Multimedia and Vision

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By , May 13, 2013

MICC Reading GroupAndy Bagdanov and I are organizing a paper reading group on Multimedia and Vision at the MICC of University of Florence.

We plan a meeting once every three weeks (approximately), usually from 12.00 to 13.30. The schedule of our meetings and the material are available on this page.

DBMM 2009 Contest

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By , October 19, 2009

DBMM 2009 Contest

MICC laboratories, Florence, 21st October 2009 (10.30-13.30). Course on Multimedia Databases (DBMM) – laboratory lecture.

  • Goal: logo recognition in web images.
  • Dataset/testset: find 2 different logos vs 100 images.
  • Evaluation metrics: recognition performances will be evaluated in terms of Precision and Recall.

Tutors: Lamberto Ballan, Lorenzo Seidenari.

Download slides Go to document (with references) | Download Software & Dataset Go to document

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