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

Showing 2650 of 525 papers

TitleStatusHype
Learning to Adversarially Blur Visual Object TrackingCode1
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object TrackingCode1
AiATrack: Attention in Attention for Transformer Visual TrackingCode1
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box EstimationCode1
Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV TrackingCode1
Joint Visual Grounding and Tracking with Natural Language SpecificationCode1
Improving Visual Object Tracking through Visual PromptingCode1
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and SegmentationCode1
LaSOT: A High-quality Large-scale Single Object Tracking BenchmarkCode1
Learning to Fuse Asymmetric Feature Maps in Siamese TrackersCode1
Global Instance Tracking: Locating Target More Like HumansCode1
Exploring Lightweight Hierarchical Vision Transformers for Efficient Visual TrackingCode1
High-Performance Long-Term Tracking with Meta-UpdaterCode1
Efficient Visual Tracking via Hierarchical Cross-Attention TransformerCode1
Explicit Visual Prompts for Visual Object TrackingCode1
Do Different Tracking Tasks Require Different Appearance Models?Code1
AutoTrack: Towards High-Performance Visual Tracking for UAV with Automatic Spatio-Temporal RegularizationCode1
Efficient Motion Prompt Learning for Robust Visual TrackingCode1
Automatic Failure Recovery and Re-Initialization for Online UAV Tracking with Joint Scale and Aspect Ratio OptimizationCode1
Exploiting Lightweight Hierarchical ViT and Dynamic Framework for Efficient Visual TrackingCode1
Fully Convolutional Online TrackingCode1
Tracking-by-Trackers with a Distilled and Reinforced ModelCode1
Transformer TrackingCode1
How to Train Your Energy-Based Model for RegressionCode1
Deep Convolutional Neural Networks for Thermal Infrared Object TrackingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ARTrack-LAUC60.3Unverified
2UNINEXT-HAUC59.3Unverified
3JointNLTAUC56.9Unverified
4OSTrackAUC55.9Unverified
5TransTAUC50.7Unverified
6AdaSwitcherAUC42Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (Panning MOVi-E)Average Jaccard61.3Unverified
2TAPIR (MOVi-E)Average Jaccard59.8Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (Panning MOVi-E)Average Jaccard57.2Unverified
2TAPIR (MOVi-E)Average Jaccard57.1Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (Panning MOVi-E)Average Jaccard84.7Unverified
2TAPIR (MOVi-E)Average Jaccard84.3Unverified
#ModelMetricClaimedVerifiedStatus
1TAPIR (MOVi-E)Average Jaccard66.2Unverified
2TAPIR (Panning MOVi-E)Average Jaccard62.7Unverified
#ModelMetricClaimedVerifiedStatus
1TATrack-LAUC71.1Unverified
#ModelMetricClaimedVerifiedStatus
1SiamFC-lu (Ours)AUC0.32Unverified
#ModelMetricClaimedVerifiedStatus
1SiamFC-lu (Ours)AUC0.66Unverified
#ModelMetricClaimedVerifiedStatus
1MDNetScore0.64Unverified
#ModelMetricClaimedVerifiedStatus
1TATrack-LACCURACY0.85Unverified