Logistics
Where: GHC 4307
When: Monday/Wednesday 1:30 PM - 2:50 PM
Instructors: Abhinav Gupta
Office Hours: By appointment
<CVPR VU Challenge for Class Projects>
Updates
Overview
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
People
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 |
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| Abhinav Gupta | Lerrel Pinto | Senthil Purushwalkam |
| Instructor | TA | TA |
| EDSH 213 | EDSH 101 | EDSH 235 |
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