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Hao Su authored and Hao Su committed Oct 15, 2024
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125 changes: 125 additions & 0 deletions cs468.css
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11 changes: 11 additions & 0 deletions head.html
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<head>

<meta http-equiv="Content-Type" content="text/html; charset=utf-8"><title>CSE152: Introduction to Computer Vision</title>

<link rel="stylesheet" type="text/css" href="cs468.css"></head>

<body>
<p>DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING</br>UNIVERSITY OF CALIFORNIA, SAN DIEGO</p>
<h1 align="center"><font color="#800000">CSE152A: Introduction to Computer Vision</font></h1>
<p></p><h2 align="center"><font color="#800000">Fall 2018</font></h2><p></p>
<br>
161 changes: 161 additions & 0 deletions index.html
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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>

<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>CSE152A: Introduction to Computer Vision</title>

<link rel="stylesheet" type="text/css" href="cs468.css">
</head>

<body>
<p>DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING</br>UNIVERSITY OF CALIFORNIA, SAN DIEGO</p>
<h1 align="center">
<font color="#800000">CSE152A: Introduction to Computer Vision</font>
</h1>
<p></p>
<h2 align="center">
<font color="#800000">Winter 2022</font>
</h2>
<p></p>
<br>

<div id="content">
<div class="underlinemenu">
<ul>
<li><a href="index.html">General Info</a></li>
<li><a href="resources.html">Resources</a></li>
<li><a href="schedule.html">Schedule &amp; Assignments</a></li>
<li><a href="https://piazza.com/class/kxxkt8n1m205nd">Piazza</a></li>
</ul>
</div>
<div class="underlinemenu"> </div>
<a name="announcements"></a>
<h3>Announcements</h3>
<ul>
<li>Welcome to the course! </li>
<li>Please sign up with <a href="https://piazza.com/class/kxxkt8n1m205nd">Piazza</a></li>
</ul>
<br>
<br>
<a name="info"></a>
<hr>
<h3>General Information</h3>
<strong>Times &amp; Places</strong>
<br>Lecture: WeFr 5:00PM - 6:20PM, Zoom, <a href="https://ucsd.zoom.us/j/94341953328">Zoom</a>
<br>Discussion: 8:00pm-9:00pm, Thu<br><br>
<a name="staff"></a>
<strong>Course Staff</strong>
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<th scope="col"><br>
</th>
<th scope="col">Name</th>
<th scope="col">Email</th>
<th scope="col">Office Hours</th>
<th scope="col">Location</th>
</tr>
</thead>
<tbody>
<tr>
<td>Instructor</td>
<td>Prof. Hao Su</td>
<td>[email protected]</td>
<td>1:00pm-2:00pm, Wed</td>
<td><a href="https://ucsd.zoom.us/my/haosuzoom">link</a></td>
</tr>
<!--
<tr>
<td>Instructor</td>
<td>Prof. Manmohan Chandraker</td>
<td>[email protected]</td>
<td>TBD</td>
<td></td>
</tr>
-->
<tr>
<td>Course Assistant</td>
<td>Yuying Yeh</td>
<td>[email protected]</td>
<td>10:00am-11:00am, Wed</td>
<td><a href="https://ucsd.zoom.us/j/4635172734">link</a></td>
</tr>
<tr>
<td>Course Assistant</td>
<td>Rui Zhu</td>
<td>[email protected]</td>
<td>2:00pm-3:00pm, Tue</td>
<td><a href="https://ucsd.zoom.us/j/95813795644">link</a></td>
</tr>
<tr>
<td>Course Assistant</td>
<td>Kunal Gupa</td>
<td>[email protected]</td>
<td>9:00am-10:00am, Fri</td>
<td><a href="https://ucsd.zoom.us/j/6282427103">link</a></td>
</tr>
<tr>
<td>Course Assistant</td>
<td>Tarun Kalluri</td>
<td>[email protected] </td>
<td>3:30pm-4:30pm, Mon</td>
<td><a href="https://ucsd.zoom.us/my/tarunkal">link</a></td>
</tr>
</tbody>
</table>

<h4>Topics</h4>
<ul>
<li>Camera Model</li>
<li>Multi-View Geometry</li>
<li>Structure from Motion</li>
<li>Optical Flow</li>
<li>Image Classification</li>
<li>Basic Convolutional Neural Network</li>
</ul>

<h4>Objectives</h4>

<p>The goal of computer vision is to compute properties of the three-dimensional world from images and video. Problems in this field include identifying the 3D shape of a scene, determining how things are moving, and recognizing familiar people and objects. This course provides an introduction to computer vision, including such topics as 3D shape reconstruction through stereo, motion estimation, and image classification. To reflect the latest progress of computer vision, we also include a brief introduction to the philosophy and basic techniques of deep learning methods.</p>

<p>Prerequisites: Linear algebra and calculus; data structures/algorithms; and Python or other programming experience.</p>

<p>Programming aspects of the assignments will be completed using Python.</p>

<p>Academic Integrity Policy: Integrity of scholarship is essential for an academic community. The University expects that both faculty and students will honor this principle and in so doing protect the validity of University intellectual work. In this class, we encourage students to form groups of two and work together on homeworks. This means that all academic work will be done by the pair of individuals to whom it is assigned, without unauthorized aid of any kind.</p>

<p>Collaboration Policy: It is expected that you complete your academic assignments in your own words (more specifically, for any write-up assignment each individual must submit an independent copy). For coding tasks, each individual must write your own copy. The assignments have been developed by the instructor to facilitate your learning and to provide a method for fairly evaluating your knowledge and abilities (not the knowledge and abilities of others). So, to facilitate learning, you are authorized to discuss assignments with others (even if he/she is not your team member); however, to ensure fair evaluations, you are not authorized to use the answers developed by another, copy the work completed by others in the past or present, or write your academic assignments in collaboration with another person.</p>

<p>If the work you submit is determined to be violating the rules, you will be reported to the Academic Integrity Office for violating UCSD's Policy on Integrity of Scholarship. In accordance with the CSE department academic integrity guidelines, students found committing an academic integrity violation will receive an F in the course.</p>

<p>Late Policy: No late day is allowed. However, <b>you can drop one out of nine assignments without penalty</b>. </p>

<h4>Homework, Exams, and Grading (tentative)</h4>
<ul>
<li>Weekly Homeworks: 80%</li>
<!--<li>The due dates of homeworks are at 11:59<b>AM</b> of Tue in the 4, 6, 8, and 10 weeks.</li>-->
<!--<li>In-class exam 5%</li>-->
<!--<li>Mid-term 20%, in the 5th week</li>-->
<li>Final Project: 20%</li>
<li>No In-class Exams</li>
</ul>
<br>

<hr>

<!--
<h4>Acknowledgements</h4>
Many of the lectures are based on the lecture slides from:
<ul>
<li><a href="http://graphics.stanford.edu/courses/cs468-17-spring/">CS468: Machine Learning on 3D Data</a></li>
<li><a href="http://cs233.stanford.edu/">CS233: Geometrical and Topological Data Analysis</a></li>
<li><a href="http://cs231n.stanford.edu/">CS231n: Convolutional Neural Networks for Visual Recognition</a></li>
<li><a href="http://people.cs.umass.edu/%7Ekalo/datadrivenshape/">Data Driven Shape Analysis and Processing</a></li>
</ul>
We would like to thank all authors for sharing their resources.
-->
</div>
</body>

</html>
37 changes: 37 additions & 0 deletions resources.html
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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<HTML>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"><title>CSE152A: Introduction to Computer Vision</title>
<link rel="stylesheet" type="text/css" href="cs468.css">
</head>
<META http-equiv="content-type" content="text/html; charset=ISO-8859-1">
<body>
<p>DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING</br>UNIVERSITY OF CALIFORNIA, SAN DIEGO</p>
<h1 align="center"><font color="#800000">CSE152A: Introduction to Computer Vision</font></h1>
<p></p><h2 align="center"><font color="#800000">Winter 2022</font></h2><p></p>
<br>
<H1 align="center">Resources</h1>
<BR>
<div id="content">
<h4> References </h4>
The book from Richard Szeliski (Second edition) is the main reference of course contents: <a href="http://szeliski.org/Book/">http://szeliski.org/Book/</a>. You can download the PDF of the full book from the book website.


<h4> Getting Help</h4>
<p align="left">The IDEA Engineering Student Center, located just off the lobby of Jacobs Hall, is a hub for student engagement, academic enrichment, personal/professional development, leadership, community involvement, and a respectful learning environment for all. The Center offers a variety of programs, listed in the IDEA Center Facebook page at http://www.facebook.com/ucsdidea/ (you are welcome to Like this page!) and the Center web site at http://idea.ucsd.edu/. The IDEA Center programs support both undergraduate students and graduate students.</p>

<h4>Diversity and Inclusion</h4>
<p align="left">We are committed to fostering a learning environment for this course that supports a diversity of thoughts, perspectives and experiences, and respects your identities (including race, ethnicity, heritage, gender, sex, class, sexuality, religion, ability, age, educational background, etc.). Our goal is to create a diverse and inclusive learning environment where all students feel comfortable and can thrive.</p>

<p align="left">Our instructional staff will make a concerted effort to be welcoming and inclusive to the wide diversity of students in this course. If there is a way we can make you feel more included please let one of the course staff know, either in person, via email/discussion board, or even in a note under the door. Our learning about diverse perspectives and identities is an ongoing process, and we welcome your perspectives and input.</p>

<p align="left">We also expect that you, as a student in this course, will honor and respect your classmates, abiding by the UCSD Principles of Community (https://ucsd.edu/about/principles.html). Please understand that others’ backgrounds, perspectives and experiences may be different than your own, and help us to build an environment where everyone is respected and feels comfortable.</p>

<p align="left">If you experience any sort of harassment or discrimination, please contact the instructor as soon as possible. If you prefer to speak with someone outside of the course, please contact the Office of Prevention of Harassment and Discrimination: https://ophd.ucsd.edu/.</p>

<h4>Students with Disabilities</h4>
<p align="left">We aim to create an environment in which all students can succeed in this course. If you have a disability, please contact the Office for Students with Disability (OSD), which is located in University Center 202 behind Center Hall, to discuss appropriate accommodations right away. We will work to provide you with the accommodations you need, but you must first provide a current Authorization for Accommodation (AFA) letter issued by the OSD. You are required to present their AFA letters to Faculty (please make arrangements to contact me privately) and to the OSD Liaison in the department in advance so that accommodations may be arranged.</p>
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