Upcoming dates: August 27: Classes start
September 3: Deadline to sign up for papers (as presenter and critic)
September 15: Project proposal

Location: NSH 3002

Time: Tuesday, Thursday 13:30-14:50

Course Description: A graduate seminar 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 professor.

Similar Classes:
Awards: At the end of the course there will be prizes for each of the following:

  • Best Blog Post
  • Best Reviewer
  • Best Research Proposal
  • Best Project