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Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval

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### Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval

Code to evaluate "Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval" (Mithun, Niluthpol C and Li, Juncheng and Metze, Florian and Roy-Chowdhury, Amit K) 2018

### Dependencies

This code is written in python. The necessary packages are below:

* Python 2.7
* PyTorch (>0.4)
* Tensorboard
* NLTK Punkt Sentence Tokenizer

### Evaluate Models

-- Download data and models from https://drive.google.com/drive/folders/1t3MwiCR72HDo6XiPvWSZpenqv4CGjnKl
-- To evaluate on MSR-VTT dataset : python test_weighted.py

### Reference 
If you use our code or models, please cite the following paper:

> @inproceedings{mithun2018learning,
  title={Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval},
  author={Mithun, Niluthpol C and Li, Juncheng and Metze, Florian and Roy-Chowdhury, Amit K},
  booktitle={ICMR},
  year={2018},
  organization={ACM}
}

--Initial code borrowed heavily from VSE++(https://github.com/fartashf/vsepp)

-- Contact: Niluthpol Chowdhury Mithun (nmith001@ucr.edu)

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