Deep Cropping via Attention Box Prediction and Aesthetics Assessment

@article{Wang2017DeepCV,
  title={Deep Cropping via Attention Box Prediction and Aesthetics Assessment},
  author={Wenguan Wang and Jianbing Shen},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={2205-2213}
}
  • Wenguan Wang, Jianbing Shen
  • Published 1 October 2017
  • Computer Science
  • 2017 IEEE International Conference on Computer Vision (ICCV)
We model the photo cropping problem as a cascade of attention box regression and aesthetic quality classification, based on deep learning. A neural network is designed that has two branches for predicting attention bounding box and analyzing aesthetics, respectively. The predicted attention box is treated as an initial crop window where a set of cropping candidates are generated around it, without missing important information. Then, aesthetics assessment is employed to select the final crop as… 
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