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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–325 of 525 papers

TitleStatusHype
Single Object Tracking Research: A Survey—0
SINT++: Robust Visual Tracking via Adversarial Positive Instance Generation—0
SOWP: Spatially Ordered and Weighted Patch Descriptor for Visual Tracking—0
Sparse2Dense: From direct sparse odometry to dense 3D reconstruction—0
Sparse Coding and Counting for Robust Visual Tracking—0
Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking?—0
Spatio-Temporal Matching for Siamese Visual Tracking—0
SPiKeS: Superpixel-Keypoints Structure for Robust Visual Tracking—0
Staged Depthwise Correlation and Feature Fusion for Siamese Object Tracking—0
State-aware Anti-drift Robust Correlation Tracking—0
STCT: Sequentially Training Convolutional Networks for Visual Tracking—0
Stochastic Channel Decorrelation Network and Its Application to Visual Tracking—0
StructBoost: Boosting Methods for Predicting Structured Output Variables—0
Structural Correlation Filter for Robust Visual Tracking—0
Structural Sparse Tracking—0
Structured Group Local Sparse Tracker—0
Structured Siamese Network for Real-Time Visual Tracking—0
Superevents: Towards Native Semantic Segmentation for Event-based Cameras—0
Superpixel Tensor Pooling for Visual Tracking using Multiple Midlevel Visual Cues Fusion—0
Synthetic data generation for end-to-end thermal infrared tracking—0
TAPL: Dynamic Part-based Visual Tracking via Attention-guided Part Localization—0
Target-Aware Deep Tracking—0
TCDCaps: Visual Tracking via Cascaded Dense Capsules—0
Distilled Siamese Networks for Visual Tracking—0
Technical Report for ReID-SAM on SkiTB Visual Tracking Challenge 2025—0
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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