SOTAVerified

Visual Object Tracking

Visual Object Tracking is an important research topic in computer vision, image understanding and pattern recognition. Given the initial state (centre location and scale) of a target in the first frame of a video sequence, the aim of Visual Object Tracking is to automatically obtain the states of the object in the subsequent video frames.

Source: Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Object Tracking

Papers

Showing 110 of 341 papers

TitleStatusHype
UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather ConditionsCode1
Mamba-FETrack V2: Revisiting State Space Model for Frame-Event based Visual Object TrackingCode1
R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement LearningCode2
Fully Spiking Neural Networks for Unified Frame-Event Object Tracking0
Progressive Scaling Visual Object Tracking0
Adapting SAM 2 for Visual Object Tracking: 1st Place Solution for MMVPR Challenge Multi-Modal Tracking0
Towards Low-Latency Event Stream-based Visual Object Tracking: A Slow-Fast ApproachCode0
CGTrack: Cascade Gating Network with Hierarchical Feature Aggregation for UAV TrackingCode0
Adversarial Attack for RGB-Event based Visual Object TrackingCode0
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual TrackingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TransVOSF-Measure (Seen)86.7Unverified
2CFBIF-Measure (Unseen)83.4Unverified
3RMNJaccard (Unseen)75.7Unverified
4KMNJaccard (Unseen)75.3Unverified
5PTSNetJaccard (Seen)73.5Unverified
6OSVOSO (Average of Measures)58.8Unverified
7OnAVOSO (Average of Measures)55.2Unverified
8SiamMaskO (Average of Measures)52.8Unverified
9OSMNO (Average of Measures)51.2Unverified