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 126–150 of 525 papers

TitleStatusHype
DreamTrack: Dreaming the Future for Multimodal Visual Object Tracking—0
Diff-Tracker: Text-to-Image Diffusion Models are Unsupervised Trackers—0
3D Visual Tracking Framework with Deep Learning for Asteroid Exploration—0
Hallucinated Adversarial Learning for Robust 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
Derivation of a Constant Velocity Motion Model for Visual Tracking—0
Depth-Adaptive Computational Policies for Efficient Visual Tracking—0
Active Learning for Deep Visual Tracking—0
Hedged Deep Tracking—0
Higher Performance Visual Tracking with Dual-Modal Localization—0
Deformable Parts Correlation Filters for Robust Visual Tracking—0
DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking—0
Adversarial Feature Sampling Learning for Efficient Visual Tracking—0
Deep Tracking: Visual Tracking Using Deep Convolutional Networks—0
DeepSORT-Driven Visual Tracking Approach for Gesture Recognition in Interactive Systems—0
Beyond Background-Aware Correlation Filters: Adaptive Context Modeling by Hand-Crafted and Deep RGB Features for Visual Tracking—0
Generic Multiview Visual Tracking—0
Deep Reinforcement Learning with Iterative Shift for Visual Tracking—0
Deep Reinforcement Learning for Visual Object Tracking in Videos—0
BASE: Probably a Better Approach to Multi-Object Tracking—0
Deep Motion Features for Visual Tracking—0
Deep Meta Learning for Real-Time Target-Aware Visual Tracking—0
Action Recognition with Joint Attention on Multi-Level Deep Features—0
3DMODT: Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds—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