Corpus ID: 17041200

Weakly-supervised Discriminative Patch Learning via CNN for Fine-grained Recognition

@article{Wang2016WeaklysupervisedDP,
  title={Weakly-supervised Discriminative Patch Learning via CNN for Fine-grained Recognition},
  author={Y. Wang and V. Morariu and L. Davis},
  journal={ArXiv},
  year={2016},
  volume={abs/1611.09932}
}
  • Y. Wang, V. Morariu, L. Davis
  • Published 2016
  • Computer Science
  • ArXiv
  • Research on fine-grained recognition has recently shifted from multistage frameworks to convolutional neural networks (CNN) that are trained end-to-end. [...] Key Method We achieve this by designing a novel asymmetric two-stream network architecture with supervision on convolutional filters and a nonrandom way of layer initialization. Experimental results show that our approach is able to find high-quality discriminative patches and achieves state-of-the-art on two publicly available fine-grained recognition…Expand Abstract
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