This is the official implementation of my paper: Audio-Visual Out-Of-Distribution for Generalized Zero-shot Learning, which has been accepted to The 35th British Machine Vision Conference (BMVC2024).
Install the required packages using the following command:
conda env create -f AVOOD_env.yml
We adopted the same dataset as AVCA-GZSL, which can be found in here.
The unzipped files should be placed in the avgzsl_benchmark_datasets/
folder in the root directory of the project.
To train and test the model, run the following command:
python main.py config/ucf_test.yaml
python main.py config/activity_test.yaml
python main.py config/vgg_test.yaml
or uniformly modify and run the run_avood.sh
script.
If you find this code useful, please consider citing our paper:
@inproceedings{wen2024bmvc,
title={Audio-Visual Out-Of-Distribution for Generalized Zero-shot Learning},
author={Liuyuan, Wen},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
year={2024}
}