quarter CNN: Faster R-CNN
Автор: Shih-Shinh Huang
Загружено: 2020-07-11
Просмотров: 2567
This lecture introduces an object detector called Faster R-CNN.
It was proposed in the paper entitled as "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Network”, NIPS, 2015, and IEEE Trans. on PAMI, 2017.
The outline of this lecture includes:
(1) Introduction about what object detection is, the Faster R-CNN background, and its architecture overview.
(2) Network ingredients about the components of Faster R-CNN including region proposal network, RoI pooling, and detection network.
(3)Faster R-CNN training about the training steps and two defined loss functions including RPN loss and detection loss.
0:00 Outline
1:12 About Object Detection
1:49 Background
3:25 Architecture Overview
6:58 Region Proposal Network(RPN)
11:01 RoI Pooling
12:15 Detection Network
14:57 Training Overview
16:41 RPN Loss
20:13 Detection Loss
Any comments are welcome. (email: [email protected])
All resources are available on the website (http://quarter.tw)
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