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
Show:102550
← PrevPage 1 of 35Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MCITrack-L384AUC65.3Unverified
2SPMTrack-GAUC64.7Unverified
3SPMTrack-LAUC63.7Unverified
4MCITrack-B224AUC62.9Unverified
5LoRAT-g-378AUC62.7Unverified
6LoRAT-L-378AUC62.3Unverified
7SPMTrack-BAUC62Unverified
8ODTrack-LAUC61.7Unverified
9ARTrackV2-LAUC61.6Unverified
10ODTrack-BAUC60.9Unverified