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 351–400 of 525 papers

TitleStatusHype
Visual Object Tracking in First Person Vision—0
Visual object tracking performance measures revisited—0
Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook—0
Visual tracking brain computer interface—0
Visual Tracking by means of Deep Reinforcement Learning and an Expert Demonstrator—0
Visual Tracking Using Attention-Modulated Disintegration and Integration—0
Visual Tracking using Particle Swarm Optimization—0
Visual Tracking Using Pertinent Patch Selection and Masking—0
Visual Tracking Using Sparse Coding and Earth Mover's Distance—0
Visual Tracking via Boolean Map Representations—0
Visual Tracking via Dynamic Graph Learning—0
Visual Tracking via Dynamic Memory Networks—0
Visual Tracking via Locality Sensitive Histograms—0
Visual Tracking via Nonnegative Regularization Multiple Locality Coding—0
Visual Tracking via Probability Continuous Outlier Model—0
Visual Tracking via Reliable Memories—0
Visual Tracking via Shallow and Deep Collaborative Model—0
Visual Tracking via Spatially Aligned Correlation Filters Network—0
Visual Tracking With Fully Convolutional Networks—0
VITAL: VIsual Tracking via Adversarial Learning—0
VLM Can Be a Good Assistant: Enhancing Embodied Visual Tracking with Self-Improving Vision-Language Models—0
Who did What at Where and When: Simultaneous Multi-Person Tracking and Activity Recognition—0
Multiple Feature Fusion via Weighted Entropy for Visual Tracking—0
Multiple Instance Filtering—0
Multi-Task Correlation Particle Filter for Robust Object Tracking—0
Multi-task Learning for Joint Re-identification, Team Affiliation, and Role Classification for Sports Visual Tracking—0
Multivariate Uncertainty in Deep Learning—0
Non-rigid Object Tracking via Deep Multi-scale Spatial-temporal Discriminative Saliency Maps—0
Now you see me: evaluating performance in long-term visual tracking—0
Object-Adaptive LSTM Network for Real-time Visual Tracking with Adversarial Data Augmentation—0
Object Tracking via Dynamic Feature Selection Processes—0
Object Tracking via Non-Euclidean Geometry: A Grassmann Approach—0
Occlusion-aware Visual Tracker using Spatial Structural Information and Dominant Features—0
Occlusion-Robust Online Multi-Object Visual Tracking using a GM-PHD Filter with CNN-Based Re-Identification—0
Occlusion-robust Visual Markerless Bone Tracking for Computer-Assisted Orthopaedic Surgery—0
Once for All: a Two-flow Convolutional Neural Network for Visual Tracking—0
One-Shot Adversarial Attacks on Visual Tracking With Dual Attention—0
Online Decision Based Visual Tracking via Reinforcement Learning—0
Online Hybrid Lightweight Representations Learning: Its Application to Visual Tracking—0
Online Metric-Weighted Linear Representations for Robust Visual Tracking—0
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network—0
Online Unsupervised Feature Learning for Visual Tracking—0
Online Visual Tracking with One-Shot Context-Aware Domain Adaptation—0
On the connections between saliency and tracking—0
Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking—0
Part-Based Visual Tracking with Online Latent Structural Learning—0
Partial Occlusion Handling for Visual Tracking via Robust Part Matching—0
Particle filter re-detection for visual tracking via correlation filters—0
Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking—0
Patchwise object tracking via structural local sparse appearance model—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