Target

Duration

20 hours

Instructors

Francesca Odone
UniGe | MaLGa & DIBRIS francesca.odone@unige.it
Nicoletta Noceti
UniGe | MaLGa & DIBRIS nicoletta.noceti@unige.it

When

Jul 12 2022 , Jul 20 2022

Where

UniGe | DIBRIS, Via Dodecaneso 35, 16146 Genova, Room 506

Important Dates

Application deadline [EXTENDED]: May 31st
Notifications of acceptance: by June 16th
The school will be held in person

Abstract

Visual perception, as a key element of Artificial Intelligence, allows us to build smart systems sensitive to surrounding environments, interactive robots, video-cameras with real time algorithms running on board. With similar algorithms, our smart-phones can log us in by recognizing our face, read text automatically, improve the quality of the photos we shoot. At the core of these applications are computer vision models, often boosted by machine learning algorithms.

This crash course is conceived as a complement to the “Deep Learning: Hands on introduction” course (henceforth DL) although it can be taken independently.

It covers the basic principles of computer vision and visual perception in artificial agents, including theoretical classes, application examples, hand-on activities.
Within CVCC, we present elements of classical computer vision (introduction to image processing, feature detection, depth estimation, motion analysis).
At the same time, by borrowing from DL, we also present deep learning approaches to computer vision problems such as image classification, detection and semantic segmentation.

The program is integrated with that of DL and the contents of the two courses are complementary. Although this is not mandatory, students are encouraged to take both courses.

Tue 12/07 9.00-09.30 Welcome
Tue 12/07 09.30-11.00 Class Introduction to Computer Vision
Tue 12/07 11.30-13.00 Class Machine learning and Deep learning, Introduction to digital signals and images
Tue 12/07 14.30-16.00 Lab I NNs on images
Wed 13/07 9.30-11.00 Class Image filters and features
Wed 13/07 11.30-13.00 Lab II Image filtering
Thu 14/07 9.30-13.00 Class Convolutional Neural Networks and their applications to image classification tasks
Thu 14/07 14:30-16.00 Lab III CNNs
Fri 15/07 9.30-13.00 Class Motion and depth estimation from images and image sequences
Fri 15/07 14.30-16.00 Lab IV Motion/depth
Format TBA Group project Optional activity for students willing to give an exam
Format TBA Group project Optional activity for students willing to give an exam

Once accepted, each candidate has to follow the instructions in the acceptance email and proceed with the payment. The registration fee is non-refundable.

Fees
AIDA students: EUR 30
Non-UniGe students and postdocs: EUR 50
professors: EUR 100
professionals, in person: EUR 400
UniGe students and postdocs: free

To apply, complete the application form

Giulia Casu
UniGe | MaLGa & DIBRIS giulia.casu@ext.unige.it

Slides and readings will be provided.

E. Trucco, A. Verri Introductory Techniques for 3-D Computer Vision Prenctice Hall 1998
R. Szeliski Computer Vision: Algorithms and Applications https://szeliski.org/Book/
I. Goodfellow, Y. Bengio, A. Courville Deep Learning https://www.deeplearningbook.org/