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 226–250 of 525 papers

TitleStatusHype
Learning Localization-aware Target Confidence for Siamese Visual Tracking—0
Development of a N-type GM-PHD Filter for Multiple Target, Multiple Type Visual Tracking—0
Adversarial Semi-Supervised Multi-Domain Tracking—0
CREST: Convolutional Residual Learning for Visual Tracking—0
Learning Online for Unified Segmentation and Tracking Models—0
Adaptive Objectness for Object Tracking—0
Learning Robotic Manipulation through Visual Planning and Acting—0
Learning Rotation for Kernel Correlation Filter—0
Diff-Tracker: Text-to-Image Diffusion Models are Unsupervised Trackers—0
Measurement-wise Occlusion in Multi-object Tracking—0
Direct Visual-Inertial Odometry with Semi-Dense Mapping—0
Accurate Bounding-box Regression with Distance-IoU Loss for Visual Tracking—0
Learning Support Correlation Filters for Visual Tracking—0
CRACT: Cascaded Regression-Align-Classification for Robust Visual Tracking—0
FPGA-based Acceleration System for Visual Tracking—0
Counterfactual Reasoning about Intent for Interactive Navigation in Dynamic Environments—0
Learning Target-oriented Dual Attention for Robust RGB-T Tracking—0
Machine learning methods for the detection of polar lows in satellite mosaics: major issues and their solutions—0
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks—0
Learning to track on-the-fly using a particle filter with annealed- weighted QPSO modeled after a singular Dirac delta potential—0
Learning to Update for Object Tracking with Recurrent Meta-learner—0
Fast Tracking via Spatio-Temporal Context Learning—0
Learning Tracking Representations from Single Point Annotations—0
Correlation Tracking via Robust Region Proposals—0
Faster Spatially Regularized Correlation Filters 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