Scaling Object Detection by Transferring Classification Weights

@article{Kuen2019ScalingOD,
  title={Scaling Object Detection by Transferring Classification Weights},
  author={Jason Kuen and Federico Perazzi and Zhe L. Lin and Jianming Zhang and Yap-Peng Tan},
  journal={2019 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2019},
  pages={6043-6052}
}
Large scale object detection datasets are constantly increasing their size in terms of the number of classes and annotations count. Yet, the number of object-level categories annotated in detection datasets is an order of magnitude smaller than image-level classification labels. State-of-the art object detection models are trained in a supervised fashion and this limits the number of object classes they can detect. In this paper, we propose a novel weight transfer network (WTN) to effectively… Expand
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