Incorporating intra-class variance to fine-grained visual recognition

@article{Em2017IncorporatingIV,
  title={Incorporating intra-class variance to fine-grained visual recognition},
  author={Yan Em and Feng Gao and Yihang Lou and Shiqi Wang and Tiejun Huang and Ling-yu Duan},
  journal={2017 IEEE International Conference on Multimedia and Expo (ICME)},
  year={2017},
  pages={1452-1457}
}
  • Yan EmFeng Gao Ling-yu Duan
  • Published 1 March 2017
  • Computer Science
  • 2017 IEEE International Conference on Multimedia and Expo (ICME)
Fine-grained visual recognition aims to capture discriminative characteristics amongst visually similar categories. The state-of-the-art research work has significantly improved the fine-grained recognition performance by deep metric learning using triplet network. However, the impact of intra-category variance on the performance of recognition and robust feature representation has not been well studied. In this paper, we propose to leverage intra-class variance in metric learning of triplet… 

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