This course will prepare the students in both the theoretical foundations of computer vision as well as the practical approaches to building real Computer Vision systems. This course investigates current research topics in computer vision with an emphasis on recognition tasks and deep learning. We will examine data sources, features, and learning algorithms useful for understanding and manipulating visual data. The goal of this course is to give students the background and skills necessary to perform research in computer vision and its application domains such as robotics. Students should understand the strengths and weaknesses of current approaches to research problems and identify interesting open questions and future research directions. Topics covered will include object detection and segmentation with deep networks, deep generative models for image generation, image captioning, activity recognition, video generation, deep transfer learning and few-shot learning.

AI PhD Curriculum