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Video Object Tracking On Nv Vot211

Metrics

AUC
Precision

Results

Performance results of various models on this benchmark

Paper Title
MCITrack_L38441.5054.20Exploring Enhanced Contextual Information for Video-Level Object Tracking
ProContEXT40.1054.50ProContEXT: Exploring Progressive Context Transformer for Tracking
ODTrack39.6055.80ODTrack: Online Dense Temporal Token Learning for Visual Tracking
KeepTrack39.5955.50Learning Target Candidate Association to Keep Track of What Not to Track
TATrack-L39.2953.94Target-Aware Tracking with Long-term Context Attention
ToMP-5039.2553.01Transforming Model Prediction for Tracking
Mixformer(ConvMAE)39.2354.20MixFormer: End-to-End Tracking with Iterative Mixed Attention
AiATrack38.9153.47AiATrack: Attention in Attention for Transformer Visual Tracking
OSTrack-38438.5953.06Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework
Neighbor- Track(OSTrack)38.3252.54NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets
STARK38.2651.37Learning Spatio-Temporal Transformer for Visual Tracking
SLT-TransT37.2251.70Towards Sequence-Level Training for Visual Tracking
STMTrack36.8450.34STMTrack: Template-free Visual Tracking with Space-time Memory Networks
TransT36.7951.97Transformer Tracking
TrDiMP36.6650.68Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking
RTS36.2053.68Robust Visual Tracking by Segmentation
KYS36.0248.13Know Your Surroundings: Exploiting Scene Information for Object Tracking
ARTrack-L35.9251.64Autoregressive Visual Tracking
DiMP-5035.8948.68Learning Discriminative Model Prediction for Tracking
SiamBAN-ACM35.8048.31Learning to Fuse Asymmetric Feature Maps in Siamese Trackers
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Video Object Tracking On Nv Vot211 | SOTA | HyperAI