VOT2019 Trackers repository

This page will contain source code of the trackers that participated in VOT2019 Challenge. This is an incomplete collection of trackers submitted to VOT2019. The collection contains only those submissions to VOT2019 for which we were able to obtain explicit permission from the authors (this was indicated by the authors during results submission process). In most cases the code is provided as it was submitted, in other cases some authors asked us to point the link to their own repositories. The VOT does not take any responsibility for the state of code/binaries of the trackers available here. For any additional information regarding individual trackers, please contact the corresponding authors directly.

Each tracker is referred as NAME (Appendix Nr NN), where NAME is the name given to the tracker and NN is the tracker number referred on the VOT paper.

If you have any question or suggestion, please contact us on the support forum.

Short Term (ST) Trackers

• Visual Tracking by means of Deep Reinforcement Learning and an Expert Demonstrator (A3CTD) - Appendix A.1

• Adaptive Correction Network based tracker (ACNT) - Appendix A.2

• Adversarial Learning for Tracking Objects (ALTO) - Appendix A.3

• [ANT (ANT)] - Appendix A.4

• Accurate and Robust Tracking based on Correlation filter and SiamRPN (ARTCS) - Appendix A.5

• [Scale Adaptive Mean-Shift Tracker (ASMS)] - Appendix A.6

• ATOM: Accurate Tracking by Overlap Maximization (ATOM) - Appendix A.7

• ATP: Accurate Tracking by Progressively refining (ATP) - Appendix A.8

• Channel Independent Spatially Regularized Discriminative Correlation Filter Tracker (CISRDCF) - Appendix A.9

• [Online Update Tracking Model for Discriminant Feature Learning (Cola)] - Appendix A.10

• [Discriminative Correlation Filter with Channel and Spatial Reliability (CSRDCF)] - Appendix A.11

• Discriminative Correlation Filter with Channel and Spatial Reliability C++ (CSRpp) - Appendix A.12

• Learning Features with Differentiable Closed-Form Solvers for Tracking (DCFST) - Appendix A.13

• Learning Discriminative Model Prediction for Tracking (DiMP) - Appendix A.14

• [Deformable part correlation filter tracker (DPT)] - Appendix A.15

• High Accuracy Visual Tracking with Deep Regression Networks (DRNet) - Appendix A.16

• [Flock of Trackers (FoT)] - Appendix A.17

• Fast Saliency-guided Continuous Correlation Filter-based tracker (FSC2F) - Appendix A.18

• SiamRPN with adaptive anchors and proposals (gasiamrpn) - Appendix A.19

• [Online Adaptive Hidden Markov Model for Multi-Tracker Fusion (HMMTxD)] - Appendix A.20

• SiamRPN with giou loss (iourpn) - Appendix A.21

• [Incremental Learning for Robust Visual Tracking (IVT)] - Appendix A.22

• [Kernelized Correlation Filter (KCF)] - Appendix A.23

• [L1APG (L1-APG)] - Appendix A.24

• [Local-Global Tracking tracker (LGT)] - Appendix A.25

• Learning Spatially Regularized correlation filters with Deep Features for Tracking (LSRDFT) - Appendix A.26

• Multi-Model Continuous Correlation Filter for visual tracking (M2C2F) - Appendix A.27

• MemTrack with Distractor Template Canceling (MemDTC) - Appendix A.28

• [Multiple Instance Learning tracker (MIL)] - Appendix A.29

• More precise box and accurate object tracking (MPAT) - Appendix A.30

• Part-Based Tracking by Sampling (PBTS) - Appendix A.31

• Ranking based tracking using CNNs and optical flow (RankingR) - Appendix A.32

• Ranking based tracker using CNNs (RankingT) - Appendix A.33

• ROAM++: Tracking via Resizable Response Generator and Bounding Box Regressor (ROAMpp) - Appendix A.34

• [Robust Siamese Fully Convolutional Tracker (RSiamFC)] - Appendix A.35

• SA-SIAM-R: A Twofold Siamese Network for Real-Time Object Tracking With Angle Estimation (SA-SIAM-R) - Appendix A.36

• [Cascade Siamese Conditional Random Fields Tracker (SiamCRF)] - Appendix A.37

• [Fast Siamese Conditional Random Field Tracker (SiamCRF-RT)] - Appendix A.38

• Online Deeper and Wider Siamese Networks for Real-Time Visual Tracking (SiamDW-ST) - Appendix A.39

• Siamese Fully Convolutional One-Stage Network for Short-Term Tracking (Siamfcos) - Appendix A.40

• Fully Convolutional One-Stage Siamese Network (SiamFCOSP) - Appendix A.41

• Siamese Fully Convolutional Object Tracking (SiamFCOT) - Appendix A.42

• Discriminative Siamese Embedding for Object Tracking (SiamMargin) - Appendix A.43

• SiamMask (SiamMask) - Appendix A.44

• Fitting Siamese Mask with Ellipses for Object Tracking (SiamMsST) - Appendix A.45

• SiamRPN++ (SiamRPNpp) - Appendix A.46

• [SiamRPNX (SiamRPNX)] - Appendix A.47

• SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking (SPM) - Appendix A.48

• Selective Spatial Regularization for Correlation Filter based Tracking (SSRCCOT) - Appendix A.49

• [Struck_ Structured output tracking with kernels (struck2011)] - Appendix A.50

• Semantic Tracking Network_ Tracking the Known and the Unknown by Leveraging Semantic Information (STN) - Appendix A.51

• Target-Aware Deep Tracking (TADT) - Appendix A.52

• [Temporal confidence learning based correlation filter tracker (TCLCF)] - Appendix A.53

• Tracking and Detection: A Unified Approach (TDE) - Appendix A.54

• Dynamic optimization tracking algorithm based on ATOM combined with static pictures (Trackyou) - Appendix A.55

• UInet( Single Object tracking based on Unet and IouNet (Uinet) - Appendix A.56

• [Weighted samples based CF tracker (WSCF-ST)] - Appendix A.57

Long Term (LT) Trackers

• Assisted Siamese Instance Search Tracking (ASINT) - Appendix B.1

• Complementary Local-Global Search for Robust Long-term Tracking (CLGS) - Appendix B.2

• Synergistic CooSiam Framework based on Comprehensive Template’s Feature and Detection (CooSiam) - Appendix B.3

• Fully Correlational Long-Term Tracker (Fu-CoLoT) - Appendix B.4

• long-term tracking by diving videos into successive short episodes (LT-DSE) - Appendix B.5

• mbdet (mbdet) - Appendix B.6

• Online Deeper and Wider Siamese Networks for Long-Term Visual Tracking (SiamDW-LT) - Appendix B.7

• Siamese Fully Convolutional One-Stage Network for Long-Term Tracking (Siamfcos-LT) - Appendix B.8

• Optimize SiamRPN with Random Search for Long-Term Tracking (SiamRPNsLT) - Appendix B.9

RGB-TIR Trackers

• Channel Independent Spatially Regularized Discriminative Correlation Filter Tracker (CISRDCF) - Appendix C.1

• [Fusion SiamRPN Tracker with Spatial Attention Fusion Strategy (FSRPN)] - Appendix C.2

• Gradient of Entropy Sensor based Background Trackable Tracker (GESBTT) - Appendix C.3

• Joint Modeling Motion and Appearance Cues for Robust RGB-T Tracking (JMMAC) - Appendix C.4

• [Multi-Adapter Convolutional Networks for RGBT Tracking (MANet)] - Appendix C.5

• [Multi-modal fusion for end-to-end RGB-T tracking (mfDiMP)] - Appendix C.6

• More precise box and accurate object tracking (MPAT) - Appendix C.7

• Online Deeper and Wider Siamese Networks for RGBT Visual Tracking (SiamDW-T) - Appendix C.8

RGB-D Trackers

• Accurate Tracking by Category-Agnostic Instance Segmentation for RGBD Image (ATCAIS) - Appendix D.1

• long-term tracking using depth information by diving videos into successive short episodes (LTDSEd) - Appendix D.2

• Online Deeper and Wider Siamese Networks for RGBD Visual Tracking (SiamDW-D) - Appendix D.3

• Enhance SiamMask Tracker Using RGBD Images (SiamM_Ds) - Appendix D.4