6.8300/6.8301: Advances in Computer Vision

Spring 2024

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Course Overview

This course covers fundamental and advanced domains in computer vision, covering topics from early vision to mid- and high-level vision, including basics of machine learning and convolutional neural networks for vision.


Feb 6, 2024: Welcome to 6.8300/6.8301!

Make sure to check out the course info below, as well as the schedule for updates. The course units are 3-0-9 for 6.8300 (Graduate Level, TQE Subject: Group 3 - Artifical Intelligence) and 4-0-11 for 6.8301 (Undergraduate Level, CI-M Subject). The prerequisites of this course are (6.1200 or 6.3700) and (18.06 or 18.C06). Good luck with your semester!
Classroom recordings will be posted here.

Course Information

Course Instructors

CI-M Instructors

Amy Carleton

Elena Kalodner-Martin
Thomas Pickering
Emily Robinson

Kristen Starkowski

Administrative Assistant

Taylor Braun

Teaching Assistants

Please use the course Piazza page for all communication with the teaching staff.

Sarah Alnegheimish
Hyojin Bahng

Purvaja 'Puja' Balaji
Mehul Damani

David Fang

David Forman

Poorya 'Pourya' Habibzadeh
Ariba Khan

Yingcheng Liu

Joanna Materzynska
Safa C. Medin

Kartikesh Mishra

McKinley Polen

Ishana Shastri

Demircan Tas

Clinton Wang

Sarah Zhang

Time and Classroom

01:00 pm - 2:30 pm every Tuesday and Thursday in 26-100.

Office Hours (All times in ET)

Please direct all problem set questions to TAs rather than instructors!


Sara: Monday 9am-10am, 45-741H (office)
Kaiming: Fri 11am-12pm, 45-701H (office)
Vincent: TBA
Mina: Monday 10am-11am (see Canvas for zoom link)


Room 24-310 unless note zoom below
Which TA for which OH is tracked on the TA OH calendar.

Mondays 2pm – 5pm
Tuesdays 10am-12pm and 2:30pm – 4:30pm
Wednesdays 9am-10am and 11am-12pm Both on zoom:
Thursdays 9am-10am and 3pm-5pm
Fridays 9am-1pm
Psets: 60%
Note: All psets are weighted equally.
Final project: 40%
Note: For 6.8301 students, a quarter of the final project grade (i.e., 10% of the course grade) will be based on participation in communication recitations (attendance is mandatory) and specific CI-M related tasks (relating mostly to the project proposal) as part of the CI-M requirement for the course. Failure to complete the CI-M component will result in a failing grade for 6.8301 students.