Learning shared representations for object recognition
author:
Antonio Torralba,
MIT - Massachusetts Institute of Technology
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| 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 |
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Interesting advanced in the recognition of images, less pixels, more cheap. Keep going, and it will be better.