• Course overview
• Student survey (average evaluation: 1.25)
• Dean's award
• Resources
• Schedule
• Deep Learning book (Goodfellow et al.)
• VIR FAQ

In order to minimize the risk of spreading the coronavirus, contact (classroom) teaching has been replaced by distant teaching, see regularly updated list of coronavirus news for more details.

• Lectures are taught online using BBB client which runs directly in the web browser. All students will receive an email invitation with the link to the conference room. Lectures are recorded and made available here.
• Labs are taught online or replaced by offline tutorials. Students will be informed about the form of each particular lab not later than the beginning of the corresponding week.

The lectures takes place in KN:E-301 on Monday 14:30-16:00. The labs will take place on Monday, Tuesday and Wednesday, see schedule for details. The first 7 weeks will be focused on lectures, tests and homework, the remaining 7 weeks are devoted to the semestral work. Lecture in the 13th week is devoted to exam test. The last lecture is poster session, where each team presents its semestral work to others. The points are divided into homework (25), semestral work (35), test T1 (20), exam test (20) .

Minimum credit requirements:

• achieve at least one point from each homework
• achieve at least one point from exam test

The final grade will be determined by the total number of points according to the following table

There will be two automatically evaluated homeworks in total. Maximum number of points in total from both homeworks is 25. All homeworks will be assigned during the labs, see labs schedule for the assignment dates. The submission of each homework has strict deadline.

Each semestral work will be solved by the team of three students. Larger or smaller groups will be allowed under certain circumstances. The maximum number of points for the semestral work is 35. There will be a limited list of topics provided by lab tutors, however students are strongly encouraged to come up with their own SW topic. We offer additional points (max. +5), to those teams who come up with an original idea, which will be approved as SW topic during the 7th week labs. If maximum capacity of a lab tutor topic is reached, the assignment will be based on the average number of points achieved by all team members so far.

Lab tutor's topics:

• topics/supervisors officially assigned during the labs in the 7th week.
• limited capacity ⇒ assignment based on the average number of points of all team members achieved so far.
• progress will be monitored based on the individual agreement between the team and the supervisor.
• Semestral work topics

own topics:

• unlimited capacity ⇒ available for all students
• supervisor is the lab tutor responsible for particular labs as follows: Patrik+Teymur for Monday's labs, Patrik for Tuesday's labs and Teymur for Wednesday's labs
• choice of the topic is part of the evaluation process
• milestone(12th week): preliminary results demonstrated.

The presentation takes place in the 14 week. The work will be presented to all students on the poster session during the Monday lecture. In addition to this, there will be 10 minute long oral presentations, which will take place during the labs. Evaluation is based on the supervisor's, lecturer's and student's voting as follows:

• 20 from supervisors
• 10 from lecturers
• 5 from other students

There will be two assessments in total: a mid-term and an exam. These are worth 20 points each, giving a maximum of 40 achievable points in total. Both will take place during Monday Lectures, see schedule for planned weeks. Competencies required for passing the test will be summarized in the end of each lecture.

Karel Zimmermann is the main lecturer of ViR. He is currently associate professor at the Czech Technical University in Prague. He received his PhD degree in cybernetics in 2008. He worked as postdoctoral researcher with the Katholieke Universiteit Leuven (2008-2009) in the group of prof Luc van Gool. His current H-index is 13 (google-scholar) and he serves as a reviewer for major journals such as TPAMI or IJCV and conferences such as CVPR, ICCV, IROS. He received the best lecturer award in 2018, the best reviewer award at CVPR 2011 and the best PhD work award in 2008. His journal paper has been selected among 14 best research works representing Czech Technical University in the government evaluation process (RIV). Since 2010 he has been chair of Antonin Svoboda Award (http://svobodovacena.cz). He was also with the Technological Education Institute of Crete (2001), with the Technical University of Delft (2002), with the University of Surrey (2006). His current research interests include learnable methods for robotics.

Teymur Azayev is one of the two VIR lab organizers. He is the third year PhD student at the Department of Cybernetics. His current interests include dynamic robot locomotion using deep learning.

Patrik Vacek is the second of the two VIR lab organizers. He is the second year PhD student at the Department of Cybernetics. His main research interests include deep learning for self-driving cars.

We want students to work individually, therefore any plagiarism in codes, homework or reports will be punished. We strongly urge each student to read what is/is not plagiarism - we believe that many students will be surprised. In any case, it is not permitted to use the work of your colleagues or predecessors. Each student is responsible for ensuring that his work does not get into the hands of other colleagues. In the case of multiple submission of the same work, all involved students will be penalized, including those who gave the work available to others.

The above does not apply to semestral works (2nd part of the semester) in which you will be working as a team and can cooperate between teams as well.