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ICCV2021 Vector-Decomposed Disentanglement
Vector-Decomposed Disentanglement for Domain-Invariant Object Detection
Datasets
Daytime-Sunny, Dusk-Rainy, and Night-Rainy
[Models]
Based on BDD-100k dataset, we construct three datasets with different weather conditions. Particularly, Daytime-Sunny contains 27,708 daytime-sunny images. Dusk-Rainy contains 3,501 images. Night-Rainy contains 2,494 images.
Training
CUDA_VISIBLE_DEVICES=4 python da_train_net_gl.py --max_epochs 20 --cuda --dataset dc --dataset_t nr --bs 1 --da_use_contex --lc --gc
Testing
CUDA_VISIBLE_DEVICES=4 python test_SW_ICR_CCR_gl.py --cuda --modelname output_path --dataset nr --gc --lc --model_dir model_name
Citation
If you find this repository useful for your work, please cite as follows:
@article{wu2021vector,
title={Vector-Decomposed Disentanglement for Domain-Invariant Object Detection},
author={Wu, Aming and Liu, Rui and Han, Yahong and Zhu, Linchao and Yang, Yi},
journal={IEEE International Conference on Computer Vision (ICCV)},
year={2021}
}