Triplet-Center Loss for Multi-view 3D Object Retrieval

@article{He2018TripletCenterLF,
  title={Triplet-Center Loss for Multi-view 3D Object Retrieval},
  author={Xinwei He and Yang Zhou and Zhichao Zhou and Song Bai and Xiang Bai},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={1945-1954}
}
  • Xinwei He, Yang Zhou, X. Bai
  • Published 16 March 2018
  • Computer Science
  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Most existing 3D object recognition algorithms focus on leveraging the strong discriminative power of deep learning models with softmax loss for the classification of 3D data, while learning discriminative features with deep metric learning for 3D object retrieval is more or less neglected. In the paper, we study variants of deep metric learning losses for 3D object retrieval, which did not receive enough attention from this area. First, two kinds of representative losses, triplet loss and… 

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