Computer Vision: Algorithms and Applications, 2nd ed.
© 2022
Richard Szeliski,
The University of Washington
Welcome to the website
(https://szeliski.org/Book)
for the second edition of my computer vision textbook,
which is now available for purchase at
Amazon,
Springer,
and other booksellers.
Todownload
an electronic version of the book, please fill in your information on
this page.
You are welcome to download the PDF website for personal use,
but not to repost it on any other website;
please post a link to
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instead.
Note that while the content of this electronic version and the hardcopy
versions are the same, the page layout is different, since
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The current download count is
128884
(since 1/23/2022).
This book is largely based on the computer vision courses that I have
co-taught at the University of Washington
(2020,
2008,
2005,
2001)
with Steve Seitz
and Harpreet Sawhney
and at Stanford (2003)
with David Fleet.
If you're curious about the process that went into writing my book,
I did an
interview with Computer Vision News (March 2022).
First edition
You can still
download the first edition or
potentially purchase it online.
The first edition is also available in
Chinese
and
Japanese
(translated by
Prof. Toru Tamaki).
Errata
If you have any comments or feedback on the book,
please send me e-mail.
Once I have accumulated enough suggestions, I will post an updated draft with
the corrections/suggestions as PDF comments.
Slide sets and lectures
There are no official slide sets to go with the book, but please feel free to look at the
University of Washington
CSE 576 (Graduate Computer Vision)
(2020
and
2008 versions)
slides that Steve Seitz and I have put together.
Additional good sources for related courses (sorted roughly by most recent first) include:
?
Noah Snavely's
CS5670 - Introduction to Computer Vision class at Cornell Tech (Spring 2023)
?
Bill Freeman, Antonio Torralba, and Phillip Isola's
6.8300/6.8301: Advances in Computer Vision class at MIT (Spring 2023)
?
Yasutaka Furukawa's
CMPT 412 - Computer Vision
class at Simon Fraser University (Spring 2023)
?
David Fouhey's
EECS 442: Computer Vision
class at the University of Michigan (Winter 2023)
?
Alyosha Efros'
CS194-26/294-26: Intro to Computer Vision and Computational Photography
class at Berkeley (Fall 2022)
?
James Hays'
CS 4476-A / 6476-A Computer Vision
class at Georgia Tech (Fall 2022)
?
James Tompkin's
CSCI 1430 Computer Vision class at Brown (Spring 2023)
?
Ioannis Gkioulekas's
15-463, 15-663, 15-862 Computational Photography class at CMU (Fall 2023)
?Matthew O'Toole's
16-385 Computer Vision class at CMU (Fall 2022)
?
Justin Johnson's
EECS 498.008 / 598.008:
Deep Learning for Computer Vision
class at the University of Michigan (Winter 2022),
which is an outstanding introduction to deep learning and visual recognition
?
Yann LeCun and Alfredo Canziani's
DS-GA 1008: Deep Learning
class at NYU (Spring 2021)
?
Luiz Velho's
Fundamentals and Trends in Vision and Image Processing
class at IMPA (Spring 2021)
?
UC Berkeley's
CS294-158-SP20:
Deep Unsupervised Learning
class (Spring 2020)
?
Scott Wehrwein's
CSCI 497P/597P - Introduction to Computer Vision
class at Western Washington University (Spring 2020)
?
Andrew Owens'
EECS 504: Foundations of Computer Vision
class at the University of Michigan (Winter 2020)
If you would like your course listed here, please contact me.
Last updated 8/21/2023