This is an advanced course that will focus on the latest research in video understanding. It consists of research paper presentations, paper discussions and a semester-long course project. Topics will include video modeling, object detection and tracking, temporal action localization, self-supervised learning, multi-modal learning, video generation, and various applications of video recognition to other domains. A background in deep learning is required.
Instructor: Gedas Bertasius
Time: Mon & Wed 12:20 pm - 1:35 pm
Location: FB 009
Office Hours: by appointment
Canvas Site: link
Class Participation: 10%
Paper Critiques: 20%
Paper Presentations: 30%
Course Project: 40%
Class Participation: Please come to class prepared for a paper discussion with your peers.
Late Submissions: The class is structured around a tight paper presentation schedule. Therefore, late assignments will not be accepted.
Academic Integrity: For your presentations and projects, you are allowed to use materials from external sources. However, you must clearly acknowledge those sources.