FasterRCNN with Multi-Stream RCNN
2019-07-08 08:48:13
We use multi-stream RCNNs to handle the proposals given by an RPN. We use multi-scale training at training time. At test time, only one single scale is used to test. We filter samples that are more than 40% occluded or smaller than 20 pixels in height. We adopt the same setting with Adapted FasterRCNN. We use VGG16 as our based network. We use pedestrian and rider to train.
| Method description: | We use multi-stream RCNNs to handle the proposals given by an RPN. We use multi-scale training at training time. At test time, only one single scale is used to test. We filter samples that are more than 40% occluded or smaller than 20 pixels in height. We adopt the same setting with Adapted FasterRCNN. We use VGG16 as our based network. We use pedestrian and rider to train. |
| Up-/Downsampling: | 1.0 |
| Computation Environment: | Intel Xeon E5-260, Nvidia TitanX |
| Computation Time: | 0.36 |