ESMTrack

Model weights for ESMTrack.

• Code: https://github.com/LiShenglana/ESMTrack
• Paper:https://arxiv.org/abs/2609.37162

Files

File	Benchmark
checkpoints/LasHeR_best_checkpoint.pth	LasHeR
checkpoints/VTUAV_best_checkpoint.pth	VTUAV
checkpoints/GTOT_best_checkpoint.pth	GTOT
checkpoints/RGBT210_best_checkpoint.pth	RGBT210
checkpoints/RGBT234_best_checkpoint.pth	RGBT234

Usage

Download the checkpoints into the project root:

hf download ShenglanLiaaa/ESMTrack --include "checkpoints/*" --local-dir .

Then test with the checkpoint of the corresponding benchmark, e.g. LasHeR:

python tracking/test.py --tracker_name esmtrack --tracker_param dropmae_256_150ep --checkpoint checkpoints/LasHeR_best_checkpoint.pth --dataset_name lasher --threads 8 --num_gpus 2

Pretrained backbone weights (e.g. DropMAE dropmae_k700_800E.pth) are not redistributed here; please download them from the DropMAE authors and put them under pretrained_networks/ (see the GitHub README).

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

@inproceedings{ESMTrack2026,
title={End-to-End Self-Supervised RGB-T Tracking without Modality Misleading},
author={Shenglan Li and Rui Yao and Kunyang Sun and Hong Jia and Yong Zhou and Javen Qinfeng Shi and Xinyu Zhang},
year={2026},
eprint={2609.37162},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2609.37162}
}