Advanced Computer Vision

CSE 252D: Advanced Computer Vision, Spring 2022

Instructor: Manmohan Chandraker
Email: mkchandraker [AT] eng [DOT] ucsd [DOT] edu

Lectures: WF 5-6:20pm on Zoom
Instructor office hours: TBD on Zoom

TAs: Meng Song (mes050@eng.ucsd.edu) and Ishit Mehta (ibmehta@eng.ucsd.edu)
TA office hours: TBD

Class discussion and message board: Piazza

Overview

This course will cover advanced concepts in computer vision. Example topics include 3D reconstruction, face recognition, object detection, semantic segmentation and domain adaptation.

Prerequisites

This is an advanced class, covering recent developments in computer vision and will extensively refer to papers. Prior background in computer vision and machine learning is required, through research experience or as covered by CSE 252A, 252B, 250B and similar offerings. Students are encouraged to contact the instructor if unsure about meeting any criteria for enrollment.

Course Format and Requirements

This will be a lecture-based course in which the majority of the material will be covered by the instructor. Students will also give a short presentation on an assigned paper. Besides, the class will have three assignments and a final exam.

Grades will be weighted as 60% for assignments, 10% for presentation and 30% for the final exam. The goal of the course is to understand the current state of computer vision and gain appreciation of its limits and potential.

Topics

The course will cover a diverse range of topics in computer vision, including:

Outline

Mar 30: Introduction Apr 01: Overview Quiz 1 Apr 06: Metric Learning Apr 08: Learning correspondence Apr 13: Optical Flow Apr 15: Learning optical Flow Apr 20: Structure from Motion Apr 22: Learning Structure from Motion Apr 27: Practical Structure from Motion Quiz 2 Apr 29: Face Recognition: I May 05: Face Recognition: II May 06: Human Pose Estimation: I May 11: Human Pose Estimation: II May 13: Semantic segmentation: I May 18: Semantic segmentation: II May 20: Object detection: I May 25: Object detection: II May 27: Domain adaptation Jun 01: Domain adaptation: II Jun 03: Semi-supervised learning

Resources

Manmohan Chandraker
Last modified: Tue, Mar 22, 2022