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 426–450 of 525 papers

TitleStatusHype
Good Features to Correlate for Visual TrackingCode0
DCFNet: Discriminant Correlation Filters Network for Visual TrackingCode0
Efficient Version-Space Reduction for Visual Tracking—0
Real-time 3D Human Tracking for Mobile Robots with Multisensors—0
Learning Background-Aware Correlation Filters for Visual TrackingCode0
Real-time visual tracking by deep reinforced decision makingCode0
Tracking using Numerous Anchor pointsCode0
Deep Reinforcement Learning for Visual Object Tracking in Videos—0
SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility—0
Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation—0
Deep Motion Features for Visual Tracking—0
Dual Deep Network for Visual TrackingCode0
Visual motion processing and human tracking behavior—0
SANet: Structure-Aware Network for Visual Tracking—0
Convolutional Regression for Visual Tracking—0
Visual Tracking via Boolean Map Representations—0
Counterfactual Reasoning about Intent for Interactive Navigation in Dynamic Environments—0
SPiKeS: Superpixel-Keypoints Structure for Robust Visual Tracking—0
Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking—0
Object Tracking via Dynamic Feature Selection Processes—0
Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning—0
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking—0
Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedbackCode0
Learning Spatially Regularized Correlation Filters for Visual Tracking—0
Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual TrackingCode0
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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