This repository is the official implementation of paper: "PML: Progressive Margin Loss for Long-tailed Age Classification"(CVPR 2021) [Paper(CVF)] [Paper(arXiv)]
[Morph II] | [FG-NET] | [ChaLearn LAP 2015] | [IMDB-WIKI]
We use (SNMC) Single Node Multi-GPU Cards training (with DistributedDataParallel) to get better performance.
python -m torch.distributed.launch --nproc_per_node=2 --master_port 29502 ./train.py --config ./configs/chalearn/exp_margin.yml
We test while training to save the best model.
If you found this code or our work useful, please cite our paper.
@InProceedings{Deng_2021_CVPR,
author = {Deng, Zongyong and Liu, Hao and Wang, Yaoxing and Wang, Chenyang and Yu, Zekuan and Sun, Xuehong},
title = {PML: Progressive Margin Loss for Long-Tailed Age Classification},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2021},
pages = {10503-10512}
}