/AMMC

Primary LanguagePythonApache License 2.0Apache-2.0

AMMC(Augmentation by Mimicking Motion Change)

This is the official implementation of our ACM MM 2021 oral paper Do We Really Need Frame-by-Frame Annotation Datasets for Object Tracking?

visdom

Setup AMMC

  • Install AMMC
git clone https://github.com/wsumel/AMMC-Augmentation-by-Mimicking-Motion-Change-.git
cd  pytracking

      Run the install script to install the dependencies.You need to provide the ${conda_install_path} (e.g. ~/anaconda3) and the name ${env_name} for the created conda environment (e.g. pytracking).

# install dependencies
bash install.sh ${conda_install_path} ${env_name}
conda activate pytracking
  • Download AMMC Models

     Pretrain model ATOM + AMMC and Dimp + AMMC can be download from Baidu key:ammc

  • Run tracker
conda activate pytracking
cd ./pytracking
# ATOM
python run_tracker.py atom default --dataset_name dataset_name --sequence sequence --debug debug --threads threads
# Dimp
python run_tracker.py dimp dimp50 --dataset_name dataset_name --sequence sequence --debug debug --threads threads

How to reproduce our result

  • Download FAT(Few-annotation Tracking) benchmark

     Baidu key:ammc

  • Training the tracker
conda activate pytracking
# ATOM + AMMC
python run_training.py bbreg atom_default
# Dimp + AMMC
python run_training.py dimp dimp50

How to construct your own FAT benchmark

  • Download three base datasets, namely TrackingNet, GOT-10k, LaSOT

  • Setting the inital size of the FAT: fat_frame_number on ./ltr/admin/local.py

  • Run the script file and Modify the dataset path as your own

cd ./ltr/
python extract_dataset.py

Performance

  • LaSOT

    Tracker Success Score Precision Score
    ATOM (paper) 0.515 n/a
    ATOM (ammc 1) 0.476 0.465
    ATOM (ammc 3) 0.507 0.501
    ATOM (ammc 5) 0.510 0.505
    ATOM (ammc 10) 0.514 0.510
    ATOM (ammc 1-10 best) 0.514 0.510
    ATOM (ammc paper) 0.517 n/a
    DiMP50 (paper) 0.569 n/a
    DiMP50 (ammc 1) 0.524 0.502
    DiMP50 (ammc 3) 0.562 0.553
    DiMP50 (ammc 5) 0.571 0.567
    DiMP50 (ammc 10) 0.568 0.558
    DiMP50 (ammc 1-10 best) 0.571 0.567
    DiMP50 (ammc paper) 0.569 n/a

  • GOT-10k:

    Tracker Success Score (AO) SR(0.50) SR(0.75)
    ATOM (paper) 0.556 0.634 0.402
    ATOM (ammc 1) 0.515 0.614 0.311
    ATOM (ammc 3) 0.553 0.645 0.408
    ATOM (ammc 5)) 0.551 0.641 0.409
    ATOM (ammc 10) 0.549 0.636 0.408
    ATOM (ammc 1-10 best) 0.553 0.645 0.408
    ATOM (ammc paper) 0.564 0.661 0.411
    DiMP50 (paper) 0.611 0.717 0.492
    DiMP50 (ammc 1) 0.525 0.626 0.323
    DiMP50 (ammc 3) 0.581 0.680 0.446
    DiMP50 (ammc 5) 0.605 0.708 0.488
    DiMP50 (ammc 10) 0.615 0.722 0.486
    DiMP50 (ammc 1-10 best) 0.615 0.722 0.486
    DiMP50 (ammc paper) 0.622 0.731 0.494

  • TrackingNet:

    Tracker Success Score Precision Score Normalized Precision Score
    ATOM (paper) 0.703 0.648 0.771
    ATOM (ammc 1) 0.675 0.618 0.751
    ATOM (ammc 3) 0.712 0.650 0.770
    ATOM (ammc 5) 0.716 0.654 0.775
    ATOM (ammc 10) 0.713 0.650 0.768
    ATOM (ammc 1-10 best) 0.716 0.654 0.775
    ATOM (ammc paper) 0.712 0.648 0.769
    DiMP50 (paper) 0.740 0.687 0.801
    DiMP50 (ammc 1) 0.698 0.635 0.765
    DiMP50 (ammc 3) 0.740 0.682 0.795
    DiMP50 (ammc 5) 0.742 0.681 0.796
    DiMP50 (ammc 10) 0.747 0.685 0.797
    DiMP50 (ammc 1-10 best) 0.747 0.685 0.797
    DiMP50 (ammc paper) 0.746 0.687 0.797

  • OTB-100/OTB-2015:

    Tracker Success Score Precision Score
    ATOM (paper) 0.669 n/a
    ATOM (ammc 1) 0.662 0.885
    ATOM (ammc 3) 0.649 0.865
    ATOM (ammc 5) 0.638 0.858
    ATOM (ammc 10) 0.643 0.850
    ATOM (ammc 1-10 best) 0.662 0.885
    ATOM (ammc paper) 0.669 n/a
    DiMP50 (paper) 0.684 n/a
    DiMP50 (ammc 1) 0.652 0.862
    DiMP50 (ammc 3) 0.647 0.852
    DiMP50 (ammc 5) 0.643 0.850
    DiMP50 (ammc 10) 0.640 0.847
    DiMP50 (ammc 1-10 best) 0.652 0.862
    DiMP50 (ammc paper) 0.669 n/a

  • UAV

    Tracker Success Score Precision Score
    ATOM (paper) 0.644 n/a
    ATOM (ammc 1) 0.622 0.850
    ATOM (ammc 3) 0.624 0.832
    ATOM (ammc 5) 0.607 0.816
    ATOM (ammc 10) 0.620 0.837
    ATOM (ammc 1-10 best) 0.624 0.832
    ATOM (ammc paper) 0.640 n/a
    DiMP50 (paper) 0.654 n/a
    DiMP50 (ammc 1) 0.628 0.844
    DiMP50 (ammc 3) 0.643 0.856
    DiMP50 (ammc 5) 0.619 0.820
    DiMP50 (ammc 10) 0.622 0.832
    DiMP50 (ammc 1-10 best) 0.643 0.856
    DiMP50 (ammc paper) 0.667 n/a

Acknowledgments

This repo is based on Pytracking which is an excellent work