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 451–500 of 525 papers

TitleStatusHype
Visual Tracking via Probability Continuous Outlier Model—0
Towards Efficient Training with Negative Samples in Visual Tracking—0
Towards Force Sensing From Vision: Observing Hand-Object Interactions to Infer Manipulation Forces—0
Towards General Multimodal Visual Tracking—0
An Analysis of Object Representations in Deep Visual Trackers—0
Towards Real-Time Visual Tracking with Graded Color-names Features—0
Data Fusion in Neuromarketing: Multimodal Analysis of Biosignals, Lifecycle Stages, Current Advances, Datasets, Trends, and Challenges—0
Adversarial Semi-Supervised Multi-Domain Tracking—0
Adversarial Feature Sampling Learning for Efficient Visual Tracking—0
Efficient Training for Visual Tracking with Deformable Transformer—0
Efficient Version-Space Reduction for Visual Tracking—0
Efficient Scale Estimation Methods using Lightweight Deep Convolutional Neural Networks for Visual Tracking—0
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition—0
Empowering Embodied Visual Tracking with Visual Foundation Models and Offline RL—0
End-to-end feature fusion siamese network for adaptive visual tracking—0
Enforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking—0
Enhanced Transformer-Based Tracking for Skiing Events: Overcoming Multi-Camera Challenges, Scale Variations and Rapid Motion -- SkiTB Visual Tracking Challenge 2025—0
Equivalence of Correlation Filter and Convolution Filter in Visual Tracking—0
Visual Tracking via Reliable Memories—0
Visual Tracking via Shallow and Deep Collaborative Model—0
Efficient Multi-level Correlating for Visual Tracking—0
Exemplar Loss for Siamese Network in Visual Tracking—0
Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking—0
Efficient Discriminative Nonorthogonal Binary Subspace with its Application to Visual Tracking—0
A Diffusion Process on Riemannian Manifold for Visual Tracking—0
Efficient Adversarial Attacks for Visual Object Tracking—0
Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking—0
Exploring Historical Information for RGBE Visual Tracking with Mamba—0
DTLLM-VLT: Diverse Text Generation for Visual Language Tracking Based on LLM—0
FANet: Quality-Aware Feature Aggregation Network for Robust RGB-T Tracking—0
Fast Dynamic Convolutional Neural Networks for Visual Tracking—0
Faster Spatially Regularized Correlation Filters for Visual Tracking—0
DSNet: Deep and Shallow Feature Learning for Efficient Visual Tracking—0
Fast Tracking via Spatio-Temporal Context Learning—0
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks—0
FPGA-based Acceleration System for Visual Tracking—0
DreamTrack: Dreaming the Future for Multimodal Visual Object Tracking—0
Adaptive Subsampling for ROI-based Visual Tracking: Algorithms and FPGA Implementation—0
Visual Tracking via Spatially Aligned Correlation Filters Network—0
Fusion with Diffusion for Robust Visual Tracking—0
Generalized mean shift with triangular kernel profile—0
Generic Multiview Visual Tracking—0
Geometric Hypergraph Learning for Visual Tracking—0
Domain Adaptive SiamRPN++ for Object Tracking in the Wild—0
Visual Tracking With Fully Convolutional Networks—0
Adaptive Objectness for Object Tracking—0
Graph Attention Tracking—0
VITAL: VIsual Tracking via Adversarial Learning—0
Hallucinated Adversarial Learning for Robust Visual Tracking—0
Hedged Deep 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