Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection

@article{Cao2019BoxlevelSS,
  title={Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection},
  author={Yanpeng Cao and Dayan Guan and Yulun Wu and Jiangxin Yang and Yanlong Cao and Michael Ying Yang},
  journal={ArXiv},
  year={2019},
  volume={abs/1902.05291}
}
Effective fusion of complementary information captured by multi-modal sensors (visible and infrared cameras) enables robust pedestrian detection under various surveillance situations (e.g. daytime and nighttime). In this paper, we present a novel box-level segmentation supervised learning framework for accurate and real-time multispectral pedestrian detection by incorporating features extracted in visible and infrared channels. Specifically, our method takes pairs of aligned visible and… CONTINUE READING
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Unsupervised Domain Adaptation for Multispectral Pedestrian Detection

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