This advanced seminar course takes an in-depth look at latest research in computer vision and related fields. The goal of the course is to expose students to a wide range of topics and trends that include multimodal learning, language and vision, deep reinforcement learning, embodied vision, image synthesis, graph networks and intuitive physics. The students will read, present and critique a curated set of research papers, and complete a semester long project in a topic are that interests them. The course is taught by Aykut Erdem.
Instruction style: During the semester, students are responsible for studying and keeping up with the course material outside of class time. These may involve reading particular book chapters, papers or blogs and watching some video lectures. After the first three lectures, each week a student will present a paper related to the topics of the week.
Lectures: Wednesday at 09:00-11:50 (Room D5)
The course webpage will be updated regularly throughout the semester with lecture notes, presentations, and important deadlines. All other course related communications will be carried out through Piazza. Please enroll it by following the link https://piazza.com/hacettepe.edu.tr/spring2019/cmp722.
This course is designed to familiarize students to the current state of the art so a solid background in computer vision and deep learning is strongly recommended. The course is open to all graduate students in the CENG department. Non-CENG graduate students, however, should ask the course instructor for approval before the add/drop period.Prospective senior undergraduate students may sit in on the class. If you are unsure whether you have the background, consider the following list of prerequisites:
Grading for CMP722 will be based on
|Feb 27||Introduction to the course|
|Mar 6||Neural Networks Basics, Spatial Processing with CNNs|
|Mar 13||Sequential Processing with NNs, Attention||Paper selections|
|Mar 20||Discussions on project proposals|
|Apr 3||Language and vision|
|Apr 10||Deep reinforcement learning|
|Apr 17||Embodied vision|
|Apr 24||Project progress presentations|
|May 1||No class||Project progress reports due|
|May 8||Image synthesis|
|May 15||Graph networks|
|May 22||Modeling the Physical World|
|May 29||Final project presentations||Final project report due|