About this course: Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and oftenly demonstrated in movies and TV-shows example of computer vision and AI.
Who is this class for: The course is designed for people (1) who already know the basics of machine learning and deep learning (2) who have never studied image processing and computer vision and want to fill that gap (3) who want to learn how to solve computer vision problems with deep learning.
Taught by: Anton Konushin, Senior LecturerHSE Faculty of Computer Science
Taught by: Alexey Artemov, Senior LecturerHSE Faculty of Computer Science