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 Object Tracking in First Person Vision—0
Visual object tracking performance measures revisited—0
Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook—0
Visual tracking brain computer interface—0
Visual Tracking by means of Deep Reinforcement Learning and an Expert Demonstrator—0
Visual Tracking Using Attention-Modulated Disintegration and Integration—0
Visual Tracking using Particle Swarm Optimization—0
Visual Tracking Using Pertinent Patch Selection and Masking—0
Visual Tracking Using Sparse Coding and Earth Mover's Distance—0
Visual Tracking via Boolean Map Representations—0
Visual Tracking via Dynamic Graph Learning—0
Visual Tracking via Dynamic Memory Networks—0
Visual Tracking via Locality Sensitive Histograms—0
Visual Tracking via Nonnegative Regularization Multiple Locality Coding—0
Visual Tracking via Probability Continuous Outlier Model—0
Visual Tracking via Reliable Memories—0
Visual Tracking via Shallow and Deep Collaborative Model—0
Visual Tracking via Spatially Aligned Correlation Filters Network—0
Visual Tracking With Fully Convolutional Networks—0
VITAL: VIsual Tracking via Adversarial Learning—0
VLM Can Be a Good Assistant: Enhancing Embodied Visual Tracking with Self-Improving Vision-Language Models—0
Who did What at Where and When: Simultaneous Multi-Person Tracking and Activity Recognition—0
Multiple Feature Fusion via Weighted Entropy for Visual Tracking—0
Multiple Instance Filtering—0
Multi-Task Correlation Particle Filter for Robust Object 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