https://github.com/GXNU-ZhongLab/EVPTrack
https://github.com/GXNU-ZhongLab/EVPTrack
Last synced: 9 months ago
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- Host: GitHub
- URL: https://github.com/GXNU-ZhongLab/EVPTrack
- Owner: GXNU-ZhongLab
- Created: 2024-04-03T13:30:13.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-03T13:46:50.000Z (over 1 year ago)
- Last Synced: 2024-11-02T05:32:37.385Z (about 1 year ago)
- Language: Python
- Size: 1.07 MB
- Stars: 12
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-Visual-Object-Tracking - [code
README
# [AAAI'2024] - EVPTrack
The official implementation for the **AAAI 2024** paper \[[_Explicit Visual Prompts for Visual Object Tracking_](https://arxiv.org/abs/2401.03142)\].
[[Models](https://drive.google.com/drive/folders/1KqpBOGAoUrN8XCU0TkPtuF-ouAyla9kP?usp=drive_link)], [[Raw Results](https://drive.google.com/file/d/1VCWn872lerG00-I1r07BI89JFfcHarwD/view?usp=sharing)], [[Training logs](https://drive.google.com/drive/folders/1xyWi3BThfZ6WUyzRGWut_cSVdHtb4oOq?usp=drive_link)]
## Highlights
### :star2: New Explicit Visual Prompts-base Tracking Framework
EVPTrack is a simple and high performance tracker. It achieves SOTA performance on multiple benchmarks by utilizing spatio-temporal and multi-scale template information.
### :star2: Strong Performance
| Tracker | GOT-10K (AO) | LaSOT (AUC) | TrackingNet (AUC) | LaSOT_ext (AUC) | UAV123 (AUC) | TNL2K (AUC) |
|:------------:|:------------:|:-----------:|:-----------------:|:---------------:|:------------:|:-----------:|
| EVPTrack-384 | 76.6 | 72.7 | 84.4 | 53.7 | 70.9 | 59.1 |
| EVPTrack-224 | 73.3 | 70.4 | 83.5 | 48.7 | 70.2 | 57.5 |
## Install the environment
```
conda create -n evptrack python=3.8
conda activate evptrack
bash install.sh
```
## Data Preparation
Put the tracking datasets in ./data. It should look like:
```
${PROJECT_ROOT}
-- data
-- lasot
|-- airplane
|-- basketball
|-- bear
...
-- got10k
|-- test
|-- train
|-- val
-- coco
|-- annotations
|-- images
-- trackingnet
|-- TRAIN_0
|-- TRAIN_1
...
|-- TRAIN_11
|-- TEST
```
## Set project paths
Run the following command to set paths for this project
```
python tracking/create_default_local_file.py --workspace_dir . --data_dir ./data --save_dir ./output
```
After running this command, you can also modify paths by editing these two files
```
lib/train/admin/local.py # paths about training
lib/test/evaluation/local.py # paths about testing
```
## Training
Download pre-trained [MAE HiViT-Base weights](https://drive.google.com/file/d/1VZQz4buhlepZ5akTcEvrA3a_nxsQZ8eQ/view?usp=share_link) and put it under `$PROJECT_ROOT$/pretrained_networks` (different pretrained models can also be used, see [MAE](https://github.com/facebookresearch/mae) for more details).
```
python tracking/train.py \
--script evptrack --config EVPTrack-full-224 \
--save_dir ./output \
--mode multiple --nproc_per_node 4 \
--use_wandb 0
```
Replace `--config` with the desired model config under `experiments/evptrack`.
We use [wandb](https://github.com/wandb/client) to record detailed training logs, in case you don't want to use wandb, set `--use_wandb 0`.
## Test and Evaluation
- LaSOT or other off-line evaluated benchmarks (modify `--dataset` correspondingly)
```
python tracking/test.py --tracker_param EVPTrack-full-224 --dataset lasot --threads 8 --num_gpus 4
python tracking/analysis_results.py # need to modify tracker configs and names
```
- GOT10K-test
```
python tracking/test.py --tracker_param EVPTrack-full-224 --dataset got10k --threads 8 --num_gpus 4
```
- TrackingNet
```
python tracking/test.py --tracker_param EVPTrack-full-224 --dataset trackingnet --threads 8 --num_gpus 4
```
## Test FLOPs, and Speed
*Note:* The speeds reported in our paper were tested on a single RTX2080Ti GPU.
```
python tracking/profile_model.py --script evptrack --config baseline
```
## Acknowledgments
* Thanks for the [OSTrack](https://github.com/botaoye/OSTrack) and [PyTracking](https://github.com/visionml/pytracking) library, which helps us to quickly implement our ideas.
## Citation
If our work is useful for your research, please consider citing:
```Bibtex
@inproceedings{shi2024evptrack,
title={Explicit Visual Prompts for Visual Object Tracking},
author={Liangtao Shi and Bineng Zhong and Qihua Liang and Ning Li and Shengping Zhang and Xianxian Li},
booktitle={AAAI},
year={2024}
}
```