Teaching Assistant

Wang Han
Song Guanglu
Wang Cheng
Niu Yazhe

Annoucements

[June 11,2021] All courses are over. Congratulations!
[May 14, 2021] Final Project is on-going. Mini-Conference will be held on May 29th, 2021.
[Apr 16, 2021] Assignment 2 is now available. DDL: May 13th, 2021.
[Mar 15, 2021] Assignment 1 is now available. Demo code and demo dataset have been released. Final dataset and codebase will be released by Mar 19.
[Mar 09, 2021] Slides (PDF) are available in Lectures.
[Feb 18, 2021] Welcome to Advanced Computer Vision!

Course Description

This course involves computer vision, signal processing, deep learning and other fields of knowledge. It elaborates with the latest academic achievements and practical cases of industrial scenes and explain the classic and state-of-the-art methods in computer vision. By studying this course, students can learn basic theories and advanced methods in computer vision, and by understanding and exploring practical problems in the industry, enhance their cognitive ability and innovative ability to solve problems in computer vision.

Chapter 1 mainly introduces the concept of computer vision, image composition and basic image processing algorithms and introduces the neural network and deep learning framework.
Chapter 2 explains in detail the most cutting-edge research direction calculation method in the field of vision and the algorithm model optimization and performance improvement methods in visual scenes.
Chapter 3 covers the practical problems faced by computer vision and the solution ideas in combination with the specific scenes of industry.

As a computer vision course offered by university and industry, the course has four advantages:

Time and Venue

Spring Term (February - June, 2021)
Lecture:
  • Every Friday, 9:50am - 11:25am
  • Room 4203, No.4 Teaching Building
Office Hour:
  • Every Thursday, 7:00pm - 8:00pm
  • Tencent Meeting Room:785 271 5223

Contact information

Dr. Li Yali: liyali13@mail.tsinghua.edu.cn
Dr. Dai Jifeng: daijifeng@sensetime.com
Dr. Liu Yu: liuyu@sensetime.com
Dr. Li Hongyang: lihongyang@senseauto.com
Chen Qingchen: chenqingchen@sensetime.com

Textbook

Grading Policy

2 Quizzes: 20%
3 Assignments: 30%
1 Final Project: 50%



FAQ

Is this course hard for undergrad students?
The course is designed for senior undergrad and graduate students. We will show lots of interesting cases and hands-on experience about deep learning models. Some part of the lectures require calculus and linear algebra, but we will walk you through those knowledge. We think for undergrads, you will learn a lot at the end of the course through lectures, tutorials and the final project.

Can I work in groups for the Final Project?
Yes, in groups of up to three people. You can freely team up with classmates.

Is this course online for the whole semester?
Yes, this course is integrated online and offline teaching for the whole semester.Please contact TA to join the Rain Classroom if you need to participate in online coures.

Resources