Visual Learning and Recognition
- When : Monday/Wednesday 12:00 PM - 1:20PM
- Where : GHC 4307
- Instructor : Abhinav Gupta
- Office Hours : By Appointment
- A number of announcements have been posted on Piazza, please check them for important details.
- HW 2 released
- TA OH for hw1 released
- HW 1 released
- Class start
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.