The goal of Computer Vision is to enable the computer or AI agent to ‘see’ and ‘understand’ the world like if not better than human beings. To that end, the computer needs to use sensors such as RGB or depth sensors to interact with the world. It mainly includes the understanding of the environment (scene understanding), humans, and further interaction with humans. Mapping to specific computer vision problems, this course will cover advanced topics in computer vision, such as 1) Scene Understanding, 2)Graphical Models, 3)3D visual perception , 4) Human Analysis and modeling. This course will review current research literature in the above fields and update students with state-of-the-art techniques. Students will work on group projects related to concrete research problems and present their research results in the form of seminars.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Describe and analyze the main research challenges in the field of computer vision.
2. Summarize research literature and state-of-the-art techniques for solving the challenging research problems in those areas.
3. Model and formulate problems, propose effective solutions to the problem and implement algorithms using suitable programming languages.
4. Design network structure and loss functions in cases where problems need to be solved using deep learning techniques.
5. Analyze the results and effectively evaluate the results on benchmark datasets.

Field Trips

Nil

Additional Course Costs

GPU server offered by the school

Recommended Resources

Whether you are on campus or studying online, there are a variety of online platforms you will use to participate in your study program. These could include videos for lectures and other instruction, two-way video conferencing for interactive learning, email and other messaging tools for communication, interactive web apps for formative and collaborative activities, print and/or photo/scan for handwritten work and drawings, and home-based assessment.

ANU outlines recommended student system requirements to ensure you are able to participate fully in your learning. Other information is also available about the various Learning Platforms you may use.

Staff Feedback

Students will be given feedback in the following forms in this course:

• written comments
• verbal comments
• feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Introduction; Low-level vision: image defocus deblur	1
2	Low-level vision: image motion blur	1
3	Low-level vision: Bayesian image matting, Natural Image Matting	1
4	Physics-based vision: Photograph Relighting	1
5	Human Body structure: basics	2
6	Human 2D/3D pose estimation	2
7	Human 3D motion predicion	2
8	Graphical Model (A): MRF, Mean-fields, Message Passing and Loop BP	2
9	Graphical Model(B): Max flow and Graph-cut	2
10	Indoor Scene Understanding: Room Layout	3
11	3D object fitting; IKEA	3
12	Outdoor Scene Understanding: Autonomous Driving	3

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Report 1: Review papers on Low level vision	15 %	13/08/2023	01/09/2023	1,2
Report 2: Review papers on Human 2d/3D pose estimation, prediction	15 %	24/09/2023	07/10/2023	1,2
Report 3: Review papers on MRF/ 3D Scene understanding.	15 %	22/10/2023	07/11/2023	1,2
Course group project including demonstration, seminar and report	55 %	06/11/2023	20/11/2023	1,2,3,4,5

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Extenuating Circumstances Application
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Assessment Task 1

Report 1: Review papers on Low level vision

Brief Descriptions: No hurdle, conference paper format. The wording should be concise with advantages and disadvantages of the proposed idea in the paper. The student needs critical thinking.

Assessment Task 2

Report 2: Review papers on Human 2d/3D pose estimation, prediction

Brief Descriptions: No hurdle, conference paper format. The wording should be concise with advantages and disadvantages of the proposed idea in the paper. The student needs critical thinking.

Assessment Task 3

Report 3: Review papers on MRF/ 3D Scene understanding.

Brief Descriptions: No hurdle, conference paper format. The wording should be concise with advantages and disadvantages of the proposed idea in the paper. The student needs critical thinking.

Assessment Task 4

Course group project including demonstration, seminar and report

Students need to work on course group project (maximum 3 students). The evaluation includes project demonstration, seminar and report.

Project demonstration (coding framework) should show the performance of the proposed approach on the task with quantitative and qualitative results.

The report should be of conference format (8 pages, two columns, font size 10, we will provide a template for the report). We will evaluate the project based on the novelty, report clarity, results analysis

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

• Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Access and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents all ANU students