Pedestrian detection via fusional convolutional features
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Yang Dongming, Ge Shuiying
The pedestrian detection methods based on convolutional networks showed a more advantage than methods with artificial features. However, most algorithms do not achieve the desired results because they have not made full use of convolutional features. In this paper, we proposed a model called Multiple Fused CNNs, which utilizes fusional feature maps from multi-scale convolutional layers to detect pedestrians.
Pedestrian detection，Convolutional network，Multiscale，Fusional features.