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 251–275 of 525 papers

TitleStatusHype
Deep Meta Learning for Real-Time Target-Aware Visual Tracking—0
Leveraging Tacit Information Embedded in CNN Layers for Visual Tracking—0
Linearization to Nonlinear Learning for Visual Tracking—0
Deep Learning-based Spacecraft Relative Navigation Methods: A Survey—0
Deep Learning-Based Multiple Object Visual Tracking on Embedded System for IoT and Mobile Edge Computing Applications—0
Local Subspace Collaborative Tracking—0
Long-Term Correlation Tracking—0
Long-term Correlation Tracking using Multi-layer Hybrid Features in Sparse and Dense Environments—0
Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System—0
A Complementary Tracking Model with Multiple Features—0
Low-complexity Multidimensional DCT Approximations—0
Deep Flow Collaborative Network for Online Visual Tracking—0
Machine learning methods for the detection of polar lows in satellite mosaics: major issues and their solutions—0
Deep Convolutional Likelihood Particle Filter for Visual Tracking—0
MAVOT: Memory-Augmented Video Object Tracking—0
Measurement-wise Occlusion in Multi-object Tracking—0
Deep Convolutional Correlation Iterative Particle Filter for Visual Tracking—0
mID: Tracking and Identifying People with Millimeter Wave Radar—0
Minimum Uncertainty Gap for Robust Visual Tracking—0
Accurate Bounding-box Regression with Distance-IoU Loss for Visual Tracking—0
VLM Can Be a Good Assistant: Enhancing Embodied Visual Tracking with Self-Improving Vision-Language Models—0
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking—0
Unsupervised Learning of Visual Representations using Videos—0
Multi-Adapter RGBT Tracking—0
Multi-attention Associate Prediction Network 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