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 301–350 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
Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking—0
The Solution for Single Object Tracking Task of Perception Test Challenge 2024—0
The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking—0
TLPG-Tracker: Joint Learning of Target Localization and Proposal Generation for Visual Tracking.—0
Towards Distraction-Robust Active Visual Tracking—0
Towards Efficient Training with Negative Samples in Visual Tracking—0
Towards Force Sensing From Vision: Observing Hand-Object Interactions to Infer Manipulation Forces—0
Towards General Multimodal Visual Tracking—0
Towards Real-Time Visual Tracking with Graded Color-names Features—0
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition—0
Tracking Without Re-recognition in Humans and Machines—0
TracKlinic: Diagnosis of Challenge Factors in Visual Tracking—0
TrackVLA: Embodied Visual Tracking in the Wild—0
Transferring Rich Feature Hierarchies for Robust Visual Tracking—0
Transparent Object Tracking Benchmark—0
TraX: The visual Tracking eXchange Protocol and Library—0
UCT: Learning Unified Convolutional Networks for Real-time Visual Tracking—0
Understanding and Diagnosing Visual Tracking Systems—0
Unified Graph based Multi-Cue Feature Fusion for Robust Visual Tracking—0
Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark—0
Unsupervised Learning of Visual Representations using Videos—0
Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers—0
Variational Inference and Learning of Piecewise-linear Dynamical Systems—0
VideoTrack: Learning To Track Objects via Video Transformer—0
Visual motion processing and human tracking behavior—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