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 251–300 of 525 papers

TitleStatusHype
Efficient Training for Visual Tracking with Deformable Transformer—0
Efficient Version-Space Reduction for Visual Tracking—0
Empowering Embodied Visual Tracking with Visual Foundation Models and Offline RL—0
End-to-end feature fusion siamese network for adaptive visual tracking—0
Enforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking—0
Enhanced Transformer-Based Tracking for Skiing Events: Overcoming Multi-Camera Challenges, Scale Variations and Rapid Motion -- SkiTB Visual Tracking Challenge 2025—0
Equivalence of Correlation Filter and Convolution Filter in Visual Tracking—0
Exemplar Loss for Siamese Network in Visual Tracking—0
Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking—0
Exploring Historical Information for RGBE Visual Tracking with Mamba—0
FANet: Quality-Aware Feature Aggregation Network for Robust RGB-T Tracking—0
Fast Dynamic Convolutional Neural Networks for Visual Tracking—0
Faster Spatially Regularized Correlation Filters for Visual Tracking—0
Fast Tracking via Spatio-Temporal Context Learning—0
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks—0
FPGA-based Acceleration System for Visual Tracking—0
Fusion with Diffusion for Robust Visual Tracking—0
Generalized mean shift with triangular kernel profile—0
Generic Multiview Visual Tracking—0
Geometric Hypergraph Learning for Visual Tracking—0
Graph Attention Tracking—0
Hallucinated Adversarial Learning for Robust Visual Tracking—0
Hedged Deep Tracking—0
Hierarchical Convolutional Features for Visual Tracking—0
Hierarchical Feature-Aware Tracking—0
Hierarchical Instruction-aware Embodied Visual Tracking—0
Robust Visual Tracking by Motion Analyzing—0
Robust Visual Tracking Revisited: From Correlation Filter to Template Matching—0
Robust Visual Tracking Using Dynamic Classifier Selection with Sparse Representation of Label Noise—0
Robust Visual Tracking via Convolutional Networks—0
Robust Visual Tracking via Implicit Low-Rank Constraints and Structural Color Histograms—0
Robust Visual Tracking via Inverse Nonnegative Matrix Factorization—0
Robust Visual Tracking via Iterative Gradient Descent and Threshold Selection—0
Robust Visual Tracking via Statistical Positive Sample Generation and Gradient Aware Learning—0
RPT++: Customized Feature Representation for Siamese Visual Tracking—0
RPT: Learning Point Set Representation for Siamese Visual Tracking—0
RSINet: Rotation-Scale Invariant Network for Online Visual Tracking—0
SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility—0
SafeDrive: Enhancing Lane Appearance for Autonomous and Assisted Driving Under Limited Visibility—0
Saliency based Semi-supervised Learning for Orbiting Satellite Tracking—0
Saliency-Enhanced Robust Visual Tracking—0
Saliency Guided Hierarchical Robust Visual Tracking—0
SANet: Structure-Aware Network for Visual Tracking—0
Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle—0
Semi-Supervised Visual Tracking of Marine Animals using Autonomous Underwater Vehicles—0
Shallow Cue Guided Deep Visual Tracking via Mixed Models—0
Siamese Attentional Keypoint Network for High Performance Visual Tracking—0
Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking—0
SiamMan: Siamese Motion-aware Network for Visual Tracking—0
SiamTHN: Siamese Target Highlight Network for Visual Tracking—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