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iamhankai
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Description

[ACM MM 2018] Attribute-Aware Attention Model for Fine-grained Representation Learning

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Attribute-Aware Attention Model

Code for ACM Multimedia 2018 oral paper: Attribute-Aware Attention Model for Fine-grained Representation Learning

We have presented results of fine-grained classification, person re-id, image retrieval tasks, including CUB-200-2011, Market-1501, CARS196 datasets in the paper. Here is the example of fine-grained classification. For detailed results, refer to the original paper or ArXiv.

Usage

Requires: Keras 1.2.1 ("imagedataformat": "channels_first")

Run in two steps:

  1. Download CUB-200-2011 dataset here and unzip it to
    $CUB
    ; Copy file
    tools/processed_attributes.txt
    to
    $CUB
    .
  • The
    $CUB
    dir should be like this:
  1. Change
    data_dir
    in
    run.sh
    to
    $CUB
    , run the scprit
    sh run.sh
    to obtain the result.
  • Result on CUB dataset

Citation

Please use the following bibtex to cite our work:

@inproceedings{han2018attribute,
  title={Attribute-Aware Attention Model for Fine-grained Representation Learning},
  author={Han, Kai and Guo, Jianyuan and Zhang, Chao and Zhu, Mingjian},
  booktitle={Proceedings of the 26th ACM international conference on Multimedia},
  pages={2040--2048},
  year={2018},
  organization={ACM}
}

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