SOTAVerified

Visual Tracking

Visual Tracking is an essential and actively researched problem in the field of computer vision with various real-world applications such as robotic services, smart surveillance systems, autonomous driving, and human-computer interaction. It refers to the automatic estimation of the trajectory of an arbitrary target object, usually specified by a bounding box in the first frame, as it moves around in subsequent video frames.

Source: Learning Reinforced Attentional Representation for End-to-End Visual Tracking

Papers

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Showing 51–100 of 525 papers

TitleStatusHype
Tracker Meets Night: A Transformer Enhancer for UAV TrackingCode1
Target-Aware Tracking with Long-term Context AttentionCode1
Video Object Segmentation-aware Video Frame InterpolationCode1
PVT++: A Simple End-to-End Latency-Aware Visual Tracking FrameworkCode1
Transformer-based assignment decision network for multiple object trackingCode1
AiATrack: Attention in Attention for Transformer Visual TrackingCode1
Ranking-Based Siamese Visual TrackingCode1
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam SearchCode1
SparseTT: Visual Tracking with Sparse TransformersCode1
Efficient Visual Tracking via Hierarchical Cross-Attention TransformerCode1
Robust Visual Tracking by SegmentationCode1
Conditional Measurement Density Estimation in Sequential Monte Carlo via Normalizing FlowCode1
Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV TrackingCode1
Global Instance Tracking: Locating Target More Like HumansCode1
Recursive Least-Squares Estimator-Aided Online Learning for Visual TrackingCode1
Space Non-cooperative Object Active Tracking with Deep Reinforcement LearningCode1
An Informative Tracking BenchmarkCode1
SwinTrack: A Simple and Strong Baseline for Transformer TrackingCode1
SIN:Superpixel Interpolation NetworkCode1
Semantic-embedded Unsupervised Spectral Reconstruction from Single RGB Images in the WildCode1
BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D ModelsCode1
Learning to Adversarially Blur Visual Object TrackingCode1
Do Different Tracking Tasks Require Different Appearance Models?Code1
Differentiable Particle Filters through Conditional Normalizing FlowCode1
Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid LabelCode1
TrTr: Visual Tracking with TransformerCode1
SiamCorners: Siamese Corner Networks for Visual TrackingCode1
Target Transformed Regression for Accurate TrackingCode1
STMTrack: Template-free Visual Tracking with Space-time Memory NetworksCode1
Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and BenchmarkCode1
Learning Spatio-Temporal Transformer for Visual TrackingCode1
Transformer TrackingCode1
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object TrackingCode1
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual TrackingCode1
Predictive Visual Tracking: A New Benchmark and Baseline ApproachCode1
Siamese Anchor Proposal Network for High-Speed Aerial TrackingCode1
Multi-modal Visual Tracking: Review and Experimental ComparisonCode1
Online Photometric Calibration of Automatic Gain Thermal Infrared CamerasCode1
Learning to Fuse Asymmetric Feature Maps in Siamese TrackersCode1
Correlation Filters for Unmanned Aerial Vehicle-Based Aerial Tracking: A Review and Experimental EvaluationCode1
Learning Spatio-Appearance Memory Network for High-Performance Visual TrackingCode1
LaSOT: A High-quality Large-scale Single Object Tracking BenchmarkCode1
Automatic Failure Recovery and Re-Initialization for Online UAV Tracking with Joint Scale and Aspect Ratio OptimizationCode1
Towards Robust Visual Tracking for Unmanned Aerial Vehicle with Tri-Attentional Correlation FiltersCode1
Unsupervised Deep Representation Learning for Real-Time TrackingCode1
Scale Equivariance Improves Siamese TrackingCode1
Visual Tracking by TridentAlign and Context EmbeddingCode1
Tracking-by-Trackers with a Distilled and Reinforced ModelCode1
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box EstimationCode1
The Heterogeneity Hypothesis: Finding Layer-Wise Differentiated Network ArchitecturesCode1
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All datasetsTNL2KDAVISKineticsKubricRGB-StackingLaSOTOTB-100OTB-2013Second dialogue state tracking challengeTrackingNet

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ARTrack-LAUC60.3—Unverified
2UNINEXT-HAUC59.3—Unverified
3JointNLTAUC56.9—Unverified
4OSTrackAUC55.9—Unverified
5TransTAUC50.7—Unverified
6AdaSwitcherAUC42—Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (Panning MOVi-E)Average Jaccard61.3—Unverified
2TAPIR (MOVi-E)Average Jaccard59.8—Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (Panning MOVi-E)Average Jaccard57.2—Unverified
2TAPIR (MOVi-E)Average Jaccard57.1—Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (Panning MOVi-E)Average Jaccard84.7—Unverified
2TAPIR (MOVi-E)Average Jaccard84.3—Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (MOVi-E)Average Jaccard66.2—Unverified
2TAPIR (Panning MOVi-E)Average Jaccard62.7—Unverified
#ModelMetricClaimedVerifiedStatus
1TATrack-LAUC71.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SiamFC-lu (Ours)AUC0.32—Unverified
#ModelMetricClaimedVerifiedStatus
1SiamFC-lu (Ours)AUC0.66—Unverified
#ModelMetricClaimedVerifiedStatus
1MDNetScore0.64—Unverified
#ModelMetricClaimedVerifiedStatus
1TATrack-LACCURACY0.85—Unverified