Learning shared representations for object recognition
author:
Antonio Torralba,
MIT - Massachusetts Institute of Technology
You might be experiencing some problems with Your Video player.
| Slides | |
| 0:01 | Learning shared representations for object recognition |
| 0:19 | Collaborators |
| 0:37 | Standard approach for object detection |
| 1:53 | Face detection |
| 2:17 | The single class age |
| 2:35 | Multiclass object detection |
| 3:10 | Object detection and the “Head in the coffee beans problem” |
| 3:14 | “Head in the coffee beans problem” |
| 3:33 | “Head in the coffee beans problem” |
| 4:27 | Symptoms of local detectors |
| 5:27 | Failure modes for object presence detection |
| 6:13 | The system does not care about the scene, but we do… |
| 6:38 | Some symptoms of one-vs-all multiclass approaches |
| 7:49 | Some symptoms of one-vs-all multiclass approaches |
| 8:19 | Some symptoms of one-vs-all multiclass approaches |
| 8:47 | Green pastures for research in multiclass object detection |
Lecture rating
| People found this lecture: | ||
| Worth seeing | ||
| because it is: | ||
| Valuable and informative | ||
| Well presented | ||
| Easily understandable | ||
| Acceptably recorded | ||
| You need to login to cast your vote. | ||
Report a problem or upload files
If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Related content
Visitors who watched this lecture also watched...
Link this page
Would you like to put a link to this lecture on your homepage?Go ahead! Copy the HTML snippet !







Interesting advanced in the recognition of images, less pixels, more cheap. Keep going, and it will be better.