iamhankai / Attribute Aware Attention
[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 ("image_data_format": "channels_first")
Run in two steps:
- Download CUB-200-2011 dataset here and unzip it to
$CUB; Copy filetools/processed_attributes.txtto$CUB.
- The
$CUBdir should be like this:
- Change
data_dirinrun.shto$CUB, run the scpritsh run.shto 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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