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README.md

VS-CNN

This is the code for the paper:

Visual Sentiment Analysis for Review Images with Item-Oriented and User-Oriented CNN
Quoc-Tuan Truong and Hady W. Lauw
Presented at MM 2017

We provide:

If you find the code and data useful in your research, please cite:

@inproceedings{vs-cnn,
  title={Visual sentiment analysis for review images with item-oriented and user-oriented CNN},
  author={Truong, Quoc-Tuan and Lauw, Hady W},
  booktitle={Proceedings of the ACM on Multimedia Conference},
  year={2017},
}

Requirements

Training and Evaluation

  • Base model:
python train_base.py --dataset [user,business]
  • Factor model:

To train the factor models, we need pre-trained weights from the base models for initialization. If you want to save time, the weights can be downloaded from here.

python train_factor.py --dataset [user,business] --factor_layer [conv1,conv3,conv5,fc7] --num_factors 16

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