Testing and training code of paper HIGH SPEED AND ROBUST RGB-THERMAL TRACKING VIA DUAL ATTENTIVE STREAM SIAMESE NETWORK of The International Geoscience and Remote Sensing Symposium (IGARSS).

• python3.7

• cuda9.2+pytorch1.7.1(not so strict)

• Ubuntu 16.04 or newer version

• install all requirements

Update on 04/06/2022, our paper has been accepted by IGARSS 2022. Paper will be published in three months.

Update on 06/04/2022, SiamCSR详细讲解已上传至bilibili弹幕网：RGB-T跟踪算法SiamCSR代码讲解

Please mkdir 'models' at root path and download snapshots and pretrain models from Baidu Cloud Drive:https://pan.baidu.com/s/1id8wCvru8cgTe6tZynpXzA password:yl6s or Google Drive:https://drive.google.com/drive/folders/1EWGAMNGd34FEbXgVobyvZY3A5nkcUPh-?usp=sharing

python bin/my_demo.py to run demo.

Please mkdir 'dataset' at root path and download GTOT, RGB-T234 and put them into dataset directory.

python bin/my_test_rgbt.py \
        --model_path /path/to/snapshots \      #snapshot path
        --result_dir /path/to/results \        #results path
        --testing_dataset GTOT                 #testing benchmark

Please download LasHeR and put it into dataset directory.

python bin/my_train.py