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 351–375 of 525 papers

TitleStatusHype
Visual tracking brain computer interface—0
RGBT Tracking via Multi-Adapter Network with Hierarchical Divergence Loss—0
Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation—0
Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map—0
Convolutional Regression for Visual Tracking—0
Robust Object Tracking Based on Temporal and Spatial Deep Networks—0
Robust Online Multi-target Visual Tracking using a HISP Filter with Discriminative Deep Appearance Learning—0
Robust Structured Group Local Sparse Tracker Using Deep Features—0
Robust Structured Multi-task Multi-view Sparse Tracking—0
Robust Tracking Using Region Proposal Networks—0
Visual Tracking by means of Deep Reinforcement Learning and an Expert Demonstrator—0
Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks—0
Robust Visual Tracking by Motion Analyzing—0
Context-aware Visual Tracking with Joint Meta-updating—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
3DMODT: Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds—0
Visual Tracking Using Attention-Modulated Disintegration and Integration—0
Robust Visual Tracking via Convolutional Networks—0
Visual Tracking using Particle Swarm Optimization—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
Visual Tracking Using Pertinent Patch Selection and Masking—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