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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 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 Tracking—0
Progressive Scaling Visual Object Tracking—0
Adapting SAM 2 for Visual Object Tracking: 1st Place Solution for MMVPR Challenge Multi-Modal Tracking—0
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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All datasetsLaSOTGOT-10kTrackingNetLaSOT-extOTB-2015UAV123TNL2KVOT2017/18DiDiNeedForSpeedYouTube-VOS 2018AVisT

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PiVOT-LSuccess Rate62.2—Unverified
2UVLTrack-LSuccess Rate57.8—Unverified
3MixFormerL-22kSuccess Rate56—Unverified
4GRMSuccess Rate54.5—Unverified
5ToMPSuccess Rate52.5—Unverified
6STARK-ST-101Success Rate50.5—Unverified
7TransTSuccess Rate49.03—Unverified