Luc Van Gool: Catalogue data in Spring Semester 2021

Name Prof. Dr. Luc Van Gool
FieldComputer Vision
Address
Institut für Bildverarbeitung
ETH Zürich, ETF C 117
Sternwartstrasse 7
8092 Zürich
SWITZERLAND
Telephone+41 44 632 65 78
E-mailvangool@vision.ee.ethz.ch
DepartmentInformation Technology and Electrical Engineering
RelationshipFull Professor

NumberTitleECTSHoursLecturers
227-0085-07LProjects & Seminars: Deep Learning for Smartphone Apps (DLSA) Restricted registration - show details
Does not take place this semester.
Only for Electrical Engineering and Information Technology BSc.

The course unit can only be taken once. Repeated enrollment in a later semester is not creditable.
3 credits3PL. Van Gool
AbstractThe category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
ObjectiveDeep Learning with Smartphone Sensors – Programming Android Phones – Neural Networks – Keras/TensorFlow -- Projects on Smartphones.

Latest smartphone generations are equipped with computational capabilities (CPU, GPU, NPU, DSP) matching common PCs from a decade ago. Moreover, smartphones have several sensors that can acquire many useful information beyond audio and visual data, for instance where we are, what we are doing, with whom we are together, what is our body constitution, what are our needs. Based on this information our smartphone offers us the appropriate computational power to process them in loco without sending the sensor data to the cloud. This course focuses on giving the bases of machine (deep) learning and embedded systems. Students will learn the tools to implement machine/deep learning algorithms in their Android phones to be smarter. The course will end with a 4 weeks project where the students can target a specific application scenario.

The course will be taught in English.
227-0085-11LProjects & Seminars: Deep Learning for Image Manipulation (DLIM) Restricted registration - show details
Does not take place this semester.
Only for Electrical Engineering and Information Technology BSc.

The course unit can only be taken once. Repeated enrollment in a later semester is not creditable.
3 credits3PL. Van Gool
AbstractThe category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
ObjectiveDeep Learning – Image Manipulation – Image Enhancement – Image Restoration – Style Transfer – Image to Image Translation – Generative Models – TensorFlow/PyTorch – Projects

With the advent of deep learning tremendous advances were achieved in numerous areas from computer vision, computer graphics, and image processing. Using these techniques, an image can be automatically manipulated in various ways with high-quality results, often fooling the human observer. Deep learning based image processing and manipulation are being applied in a vast number of emerging technologies, including image enhancement in smartphone cameras, automated image editing, image content creation, graphics, and autonomous driving. This course focuses on the fundamentals of deep learning and image manipulation. Students will learn the tools to implement and develop deep learning solutions for a variety of image manipulation tasks. The course will end with a 4 weeks project where the students can target a specific application scenario.

The course will be taught in English.
227-0085-24LProjects & Seminars: Vision and Control in RoboCup Restricted registration - show details
Only for Electrical Engineering and Information Technology BSc.

The course unit can only be taken once. Repeated enrollment in a later semester is not creditable.
3 credits1PJ. Lygeros, L. Van Gool
AbstractThe category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
ObjectiveVision and Control in RoboCup is jointly offered by Prof. John Lygeros (IFA) and Prof. Luc Van Gool (CVL).

RoboCup is a tournament where teams of autonomous robots compete in soccer matches against each other. The ETH team NomadZ plays in the standard platform league with the humanoid NAO robot, where the focus lies on developing robust and efficient algorithms for vision, control and behavior. In this course, the basic challenges we encounter in RoboCup are presented and approached in practical exercises using MATLAB and Python. The topics cover visual localization, deep learning for object detection and reinforcement learning for control.

The course is offered to students of the 5th semester.
227-0085-31LProjects & Seminars: Vision Goes Vegas Restricted registration - show details
Only for Electrical Engineering and Information Technology BSc.

The course unit can only be taken once. Repeated enrollment in a later semester is not creditable.
2 credits2PL. Van Gool
AbstractThe category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
ObjectiveComputer Vision beschäftigt sich unter anderem damit, Maschinen zu befähigen ihre Umwelt zu sehen und das wahrgenommene Bild zu verstehen. In unserem Projekt soll ein System entwickelt werden, das Spielkarten erkennen kann und, einer guten Strategie folgend, erfolgreich Black-Jack spielen kann. Die Teilnehmer des Projektes werden kleine Teams bilden und gemeinsam mit einem Assistenten die Aufgabe erarbeiten und eine Implementierung erstellen. Am Ende des Semesters sollen die Programme im öffentlichen Wettstreit gegeneinander antreten!

Ziel des Projektes ist es, aktuelle Methoden der Computer Vision kennen zu lernen. Spielkarten, die von einer Digitalkamera in beliebiger Orientierung aufgenommen werden, müssen registriert und erkannt werden. Ein Strategiemodul kontrolliert dann die Spieltaktik aufgrund allgemeiner Regeln und dem Wissen über schon gefallene Karten. Da sehr viele verschiedene Möglichkeiten bestehen, solch ein System zu realisieren, sind der Phantasie der Teilnehmer keine Grenzen gesetzt.

Als Voraussetzungen sollte Interesse an Computer Vision mitgebracht werden und die Bereitschaft, sich in einem Team von Mitstudierenden einzubringen. Kenntnisse in C++ sind notwendig.

Dieses P&S wird in englischer Sprache durchgeführt.
227-0919-00LKnowledge-Based Image Interpretation0 credits2SL. Van Gool
AbstractWith the lecture series on special topics of Knowledge based image interpretation we sporadically offer special talks.
ObjectivePresentation and discussion of internal and external original research results on the area of image analysis, computer vision, virtual and augmented reality and physically based simulation. Following recent work in the literature.
ContentPresentation and discussion of internal and external original research results on the area of image analysis, computer vision, virtual and augmented reality and physically based simulation. Following recent work in the literature.