(16-824) Visual Learning and Recognition: Course Overview and Logistics


Where: NSH 1305
When: Monday/Wednesday 1:30 PM - 2:50 PM
Instructors: Abhinav Gupta, David Fouhey
Office Hours: By appointment


  • Assignment schedule has been posted

  • Clarification: no postings are required on piazza until the Feb 10 class, when we begin the student presentations.

  • January 11: Course Begins. We will be using Piazza for discussions. Please sign up if you haven't already done so.


Summary: A graduate course in Computer Vision with emphasis on representation and reasoning for large amounts of data (images, videos and associated tags, text, gps-locations etc) toward the ultimate goal of Image Understanding. We will be reading an eclectic mix of classic and recent papers on topics including: Theories of Perception, Mid-level Vision (Grouping, Segmentation, Poselets), Object and Scene Recognition, 3D Scene Understanding, Action Recognition, Contextual Reasoning, Image Parsing, Joint Language and Vision Models, etc. We will be covering a wide range of supervised, semi-supervised and unsupervised approaches for each of the topics above.

Prerequisites: While there are no formal prerequisites, this course assumes familiarity with computer vision (16-720 or similar) and machine learning (10-601 or similar). If you have not taken courses covering this material, consult with the instructor.

Awards: At the end of the course, we will have prizes for:

  • Best blog posts (2x)

  • Best Proposal

  • Best Project


Abhinav Gupta David Fouhey Xiaolong Wang Rohit Girdhar
EDSH 213EDSH 212EDSH 216EDSH 235

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