16-824: Visual Learning and Recognition (original) (raw)
(16-824) Visual Learning and Recognition: Course Overview and Logistics
Logistics
Where: NSH 1305
When: Monday/Wednesday 1:30 PM - 2:50 PM
Instructors: Abhinav Gupta, David Fouhey
Office Hours: By appointment
Updates
- 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.
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
 |
 |
 |
 |
|---|---|---|---|
| Abhinav Gupta | David Fouhey | Xiaolong Wang | Rohit Girdhar |
| Instructor | Instructor | TA | TA |
| EDSH 213 | EDSH 212 | EDSH 216 | EDSH 235 |
Similar Classes
- 16-824 Spring 2015 (Abhinav Gupta)
- 16-824 Fall 2013 (Abhinav Gupta)
- 16-824 Spring 2012 (Alexei Efros)
- Visual Object and Activity Recognition (Trevor Darrell and Alexei Efros, Fall 2014)
- Visual Recognition (Kristen Grauman, Texas-Austin, Fall 2012)
- Advances in Computer Vision (Antonio Torralba and Bill Freeman, MIT, Fall 2014)
- Computer Vision (Ali Farhadi, University of Washington, Winter 2014)
- Visual Scene Understanding (Derek Hoiem, UIUC, Spring 2012)
- Computer Vision: Foundations and Applications (Fei-Fei Li, Stanford, Fall 2014)