This is the official PyTorch implementation of SUE from the paper "The Hidden Power of Unpaired Data for Multimodal Learning".
To run the project, clone this repo and then create a conda environment via:
conda env create -f environment.yml
Subsequently, activate this environment:
conda activate sue
To run an example of the project on the retrieval task, follow these steps:
-
Download the model checkpoints and data encodings from here.
-
Unzip the downloaded files.
-
Locate:
- The model checkpoint file:
checkpoints_flickr30.pth
(inside thecheckpoints
folder). - The data encodings: found under
data/flickr30
.
- The model checkpoint file:
-
Run the following command:
python retrieval.py --test flickr30
- If you want to train the model from scratch, use the following command:
python retrieval.py --train flickr30