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 101–150 of 525 papers

TitleStatusHype
Multi-Granularity Language-Guided Multi-Object TrackingCode1
HIPTrack: Visual Tracking with Historical PromptsCode1
LaSOT: A High-quality Large-scale Single Object Tracking BenchmarkCode1
Learning Spatio-Temporal Transformer for Visual TrackingCode1
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and SegmentationCode1
How to Train Your Energy-Based Model for RegressionCode1
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object TrackingCode1
Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid LabelCode1
Low-Light Object Tracking: A BenchmarkCode1
Learning to Adversarially Blur Visual Object TrackingCode1
Multi-modal Visual Tracking: Review and Experimental ComparisonCode1
SiamCorners: Siamese Corner Networks for Visual TrackingCode1
TrTr: Visual Tracking with TransformerCode1
Data Fusion in Neuromarketing: Multimodal Analysis of Biosignals, Lifecycle Stages, Current Advances, Datasets, Trends, and Challenges—0
Domain Adaptive SiamRPN++ for Object Tracking in the Wild—0
Hierarchical Convolutional Features for Visual Tracking—0
BranchOut: Regularization for Online Ensemble Tracking With Convolutional Neural Networks—0
Distilling Channels for Efficient Deep Tracking—0
Hedged Deep Tracking—0
Hierarchical Feature-Aware Tracking—0
Blending of Learning-based Tracking and Object Detection for Monocular Camera-based Target Following—0
Distilling Localization for Self-Supervised Representation Learning—0
Direct Visual-Inertial Odometry with Semi-Dense Mapping—0
Diff-Tracker: Text-to-Image Diffusion Models are Unsupervised Trackers—0
Cascaded Regression Tracking: Towards Online Hard Distractor Discrimination—0
DreamTrack: Dreaming the Future for Multimodal Visual Object Tracking—0
3D Visual Tracking Framework with Deep Learning for Asteroid Exploration—0
Graph Attention 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
Hallucinated Adversarial Learning for Robust Visual Tracking—0
Hierarchical Instruction-aware Embodied Visual Tracking—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
3DMODT: Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds—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
AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility—0
Action Recognition with Joint Attention on Multi-Level Deep Features—0
Generic Multiview 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