S-DOD-CNN: Doubly Injecting Spatially-Preserved Object Information for Event Recognition

@article{Lee2020SDODCNNDI,
  title={S-DOD-CNN: Doubly Injecting Spatially-Preserved Object Information for Event Recognition},
  author={Hyungtae Lee and Sungmin Eum and Heesung Kwon},
  journal={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2020},
  pages={2128-2132}
}
  • Hyungtae Lee, Sungmin Eum, H. Kwon
  • Published 11 February 2019
  • Computer Science
  • ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
We present a novel event recognition approach called Spatially-preserved Doubly-injected Object Detection CNN (S-DOD-CNN), which incorporates the spatially preserved object detection information in both a direct and an indirect way. Indirect injection is carried out by simply sharing the weights between the object detection modules and the event recognition module. Meanwhile, our novelty lies in the fact that we have preserved the spatial information for the direct injection. Once multiple… 
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