Implementation of the paper Bridging Search Region Interaction With Template for RGB-T Tracking, CVPR 2023.
conda create -n tbsi python=3.8
conda activate tbsi
bash install.sh
Run the following command to set paths for this project
python tracking/create_default_local_file.py --workspace_dir . --data_dir ./data --save_dir ./output
After running this command, you can also modify paths by editing these two files
lib/train/admin/local.py # paths about training
lib/test/evaluation/local.py # paths about testing
Put the tracking datasets in ./data. It should look like:
${PROJECT_ROOT}
-- data
-- lasher
|-- trainingset
|-- testingset
|-- trainingsetList.txt
|-- testingsetList.txt
...
Download ImageNet or SOT pretrained weights and put them under $PROJECT_ROOT$/pretrained_models.
python tracking/train.py --script tbsi_track --config vitb_256_tbsi_32x4_4e4_lasher_15ep_in1k --save_dir ./output/vitb_256_tbsi_32x4_4e4_lasher_15ep_in1k --mode multiple --nproc_per_node 4
Replace --config with the desired model config under experiments/tbsi_track.
Put the checkpoint into $PROJECT_ROOT$/output/config_name/... or modify the checkpoint path in testing code.
python tracking/test.py tbsi_track vitb_256_tbsi_32x4_4e4_lasher_15ep_in1k --dataset_name lasher_test --threads 6 --num_gpus 1
python tracking/analysis_results.py --tracker_name tbsi_track --tracker_param vitb_256_tbsi_32x4_4e4_lasher_15ep_in1k --dataset_name lasher_test
| Model | Backbone | Pretraining | Precision | NormPrec | Success | FPS | Checkpoint | Raw Result |
|---|---|---|---|---|---|---|---|---|
| TBSI | ViT-Base | ImageNet | 64.3 | 60.8 | 51.0 | 36.2 | download | download |
| TBSI | ViT-Base | SOT | 70.2 | 66.5 | 56.5 | 36.2 | download | download |
Our project is developed upon OSTrack. Thanks for their contributions which help us to quickly implement our ideas.
If our work is useful for your research, please consider cite:
@inproceedings{hui2023bridging,
title={Bridging Search Region Interaction With Template for RGB-T Tracking},
author={Hui, Tianrui and Xun, Zizheng and Peng, Fengguang and Huang, Junshi and Wei, Xiaoming and Wei, Xiaolin and Dai, Jiao and Han, Jizhong and Liu, Si},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={13630--13639},
year={2023}
}
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