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Official repository for "GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition"

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GaitSADA

This repository contains the code for: GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition The paper submitted to IEEE MASS 2023

arxiv

overall Please visit our webpage for more detail

News

📢 [2023/09/25] Presentation at IEEE MASS 2023 (Toronto, Canada) in Session 1A: AI/ML based Smart Design 1 (9:55 - 11:05).
📢 [2023/06/26] Paper accepted to IEEE MASS 2023.

install

pip install tensorflow scikit-learn matplotlib sklearn h5py PyYAML numpy tqdm

Add ouput path

export MMWAVE_PATH=~/mmwave-data/exit/preprocessed/256_resized/

Train

  1. GaitSADA:
python3 GaitSADA.py  --train_src_days=3 --train_trg_days=3 --src_aug=1 --trgt_aug=1 --epochs=10000 --epochs_2stage=10000 --log_dir=logs/example/GaitSADA/ --notes=temperal_3_day --notes_2stage=v1
  1. Supervised Learning
python3 models/supervised.py --train_src_days=3 --epochs=5000 --log_dir=logs/example/vanilla/
  1. GAN
python3 GAN.py --train_src_days=3 --train_trg_days=3 --log_dir=logs/example/GAN
  1. GRL
python3 GRL.py --train_src_days=3 --train_con_days=3 --log_dir=logs/example/GRL --note=GRL_vanilla
  1. ADDA
python3 ADDA.py --train_src_days=3 --train_off_days=3 
  1. CDAN
python3 CDAN.py --train_src_days=3 --train_trg_days=3 --log_dir=logs/example/CDAN
  1. FixMatch
python3 FixMatch.py --train_src_days=3 --train_trg_days=3 --log_dir=logs/example/FixMatch

Parameters

Number of days of source data can be specified by

--train_src_days=3

Number of days of target data can be specified by

--train_trg_days=3 
--train_ser_days=3
--train_con_days=3
--train_off_days=3

Main Results

Result of training on 1 to 3 days on the data from laboratory location (source domain) while adapting to different 1 to 3 days data of same location (i.e., temporal target domain) and 1 to 3 days of different target locations, (i.e., server, conference, and office)

table

Licence & Acknowledgement

GaitSADA itself is released under the MIT License.


https://ekkasit.com

If you find our work useful in your research, please consider citing:

@article{pinyoanuntapong2023gaitsada,
      title={GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition}, 
      author={Ekkasit Pinyoanuntapong and Ayman Ali and Kalvik Jakkala and Pu Wang and Minwoo Lee and Qucheng Peng and Chen Chen and Zhi Sun},
      year={2023},
      eprint={2301.13384},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

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