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 401–425 of 525 papers

TitleStatusHype
Pedestrian Tracking with Monocular Camera using Unconstrained 3D Motion Model—0
PG-Net: Pixel to Global Matching Network for Visual Tracking—0
Predicting Road Surface Anomalies by Visual Tracking of a Preceding Vehicle—0
Prediction-Tracking-Segmentation—0
Probabilistic Regression for Visual Tracking—0
Progressive Multi-Stage Learning for Discriminative Tracking—0
Progressive Unsupervised Learning for Visual Object Tracking—0
Pyramid-based Visual Tracking Using Sparsity Represented Mean Transform—0
Real-time 3D Human Tracking for Mobile Robots with Multisensors—0
Real-time 'Actor-Critic' Tracking—0
Real-time face swapping as a tool for understanding infant self-recognition—0
Real-Time Part-Based Visual Tracking via Adaptive Correlation Filters—0
Real-Time Visual Object Tracking via Few-Shot Learning—0
Real-Time Visual Tracking and Identification for a Team of Homogeneous Humanoid Robots—0
Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning—0
ReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements—0
Recurrently Target-Attending Tracking—0
Region-filtering Correlation Tracking—0
Relaxed Multiple-Instance SVM with Application to Object Discovery—0
Reliable Patch Trackers: Robust Visual Tracking by Exploiting Reliable Patches—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
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
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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