Awesome
DeepCU-IJCAI19
Citation
When using this code, or the ideas of DeepCU, please cite the following paper
@INPROCEEDINGS{Verma0ZL19ijcai19,
author = {Sunny Verma and Chen Wang and Liming Zhu and Wei Liu},
title = DeepCU: Integrating both Common and Unique Latent Information for Multimodal Sentiment Analysis},
booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI} Macao},
pages = {3627--3634},
year = {2019},
}
Dependencies / Notes
DeepCU is written in python3 with some code fragments copied from DCGAN implementation from Carpedm20.
- The code is developed with Python 3.6 and TensorFlow 1.12.0 (with GPU support) on Linux
- For reasons of my convenience,
data_dir
is required to bedata_dir = ../../data
-- errors might pop-up when other directories are used. - The experiments (main.py) - loads pretrained model and executes test (i.e. prediction with our trained model). If you wish to train on your own data, please edit as deep_cu.train(FLAGS).
Future research (ideas)
- Better Fusion scheme for utilizing both common and unique latent information
- Utilize Sequence information for sentiment prediction
- Cross Data Generelaization Performance
Please contact either Sunny Verma or Wei Liu at firstname.lastname@uts.edu.au if you're interested to collaborate on this!