This project contains the pytorch implemention for Zero-Shot Logit Adjustment.
--dataroot
to your local path.Please run the following commands to test on different datasets:
The meaning of these args is
--dataset
: datasets, e.g: SUN. --attSize
: size of semantic descriptors. --nz
: size of the Gaussian noise. --syn_num
: synthetic number for each unseen class. --reatio
: hyperparameter to control the seen-unseen prior (see Sec. 4.4 of the paper)We test our method in WGAN and CE-GZSL, and here are the results.
Method | AWA2 | CUB | SUN | APY | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
AS | AU | AH | AS | AU | AH | AS | AU | AH | AS | AU | AH | |
f-CLSWGAN | 57.7 | 71.0 | 63.7 | 59.4 | 63.3 | 61.3 | 46.2 | 35.2 | 40.0 | 32.5 | 57.2 | 41.5 |
ZLAPWGAN | 65.4 | 82.2 | 72.8 | 73.0 | 64.8 | 68.7 | 50.1 | 38.0 | 43.2 | 40.2 | 53.8 | 46.0 |
CE-GZSL | 65.3 | 75.0 | 69.9 | 66.9 | 65.9 | 66.4 | 52.4 | 34.3 | 41.5 | 28.3 | 65.8 | 39.6 |
ZLAP+CE-GZSL | 64.8 | 80.9 | 72.0 | 71.2 | 66.2 | 68.6 | 50.9 | 35.7 | 42.0 | 38.3 | 60.9 | 47.0 |
If you recognize our work, please cite:
@inproceedings{ijcai2022-114,
title = {Zero-Shot Logit Adjustment},
author = {Chen, Dubing and Shen, Yuming and Zhang, Haofeng and Torr, Philip H.S.},
booktitle = {Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, {IJCAI-22}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Lud De Raedt},
pages = {813--819},
year = {2022},
month = {7},
note = {Main Track}
doi = {10.24963/ijcai.2022/114},
url = {https://doi.org/10.24963/ijcai.2022/114},
}
We acknowledge the prior works f-CLSWGAN and CE-GZSL for their contributions to our work.