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

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Showing 51–100 of 341 papers

TitleStatusHype
ProContEXT: Exploring Progressive Context Transformer for TrackingCode1
Scale Equivariance Improves Siamese TrackingCode1
Self-supervised Object Tracking with Cycle-consistent Siamese NetworksCode1
Separable Self and Mixed Attention Transformers for Efficient Object TrackingCode1
PVT++: A Simple End-to-End Latency-Aware Visual Tracking FrameworkCode1
Few-Shot Backdoor Attacks on Visual Object TrackingCode1
PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionCode1
Compact Transformer Tracker with Correlative Masked ModelingCode1
Learning Spatio-Appearance Memory Network for High-Performance Visual TrackingCode1
SPMTrack: Spatio-Temporal Parameter-Efficient Fine-Tuning with Mixture of Experts for Scalable Visual TrackingCode1
SSTVOS: Sparse Spatiotemporal Transformers for Video Object SegmentationCode1
STMTrack: Template-free Visual Tracking with Space-time Memory NetworksCode1
AAA: Adaptive Aggregation of Arbitrary Online Trackers with Theoretical Performance GuaranteeCode1
PatchNet -- Short-range Template Matching for Efficient Video ProcessingCode1
NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor TrackletsCode1
Ocean: Object-aware Anchor-free TrackingCode1
Mobile Vision Transformer-based Visual Object TrackingCode1
MambaEVT: Event Stream based Visual Object Tracking using State Space ModelCode1
Multi-modal Visual Tracking: Review and Experimental ComparisonCode1
One-Shot Video Object SegmentationCode1
Representation Learning for Visual Object Tracking by Masked Appearance TransferCode1
Learning to Adversarially Blur Visual Object TrackingCode1
Deeper and Wider Siamese Networks for Real-Time Visual TrackingCode1
Learning Spatial-Frequency Transformer for Visual Object TrackingCode1
Learning to Fuse Asymmetric Feature Maps in Siamese TrackersCode1
Deep Convolutional Neural Networks for Thermal Infrared Object TrackingCode1
Learning Spatio-Temporal Transformer for Visual TrackingCode1
Deformable Siamese Attention Networks for Visual Object TrackingCode1
Energy-Based Models for Deep Probabilistic RegressionCode1
Mamba-FETrack V2: Revisiting State Space Model for Frame-Event based Visual Object TrackingCode1
Enhancing Nighttime UAV Tracking with Light Distribution SuppressionCode1
Tracking-by-Trackers with a Distilled and Reinforced ModelCode1
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object TrackingCode1
NT-VOT211: A Large-Scale Benchmark for Night-time Visual Object TrackingCode1
HIPTrack: Visual Tracking with Historical PromptsCode1
LoReTrack: Efficient and Accurate Low-Resolution Transformer TrackingCode1
How to Train Your Energy-Based Model for RegressionCode1
Backbone is All Your Need: A Simplified Architecture for Visual Object TrackingCode1
AiATrack: Attention in Attention for Transformer Visual TrackingCode1
Explicit Visual Prompts for Visual Object TrackingCode1
All-Day Object Tracking for Unmanned Aerial VehicleCode1
Do Different Tracking Tasks Require Different Appearance Models?Code1
High-Performance Long-Term Tracking with Meta-UpdaterCode1
Improving Underwater Visual Tracking With a Large Scale Dataset and Image EnhancementCode1
Cross-Drone Transformer Network for Robust Single Object TrackingCode1
Generalized Relation Modeling for Transformer TrackingCode1
Global Instance Tracking: Locating Target More Like HumansCode1
RGBD1K: A Large-scale Dataset and Benchmark for RGB-D Object TrackingCode1
Improving Visual Object Tracking through Visual PromptingCode1
Correlation-Embedded Transformer Tracking: A Single-Branch FrameworkCode1
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All datasetsLaSOTGOT-10kTrackingNetLaSOT-extOTB-2015UAV123TNL2KVOT2017/18DiDiNeedForSpeedYouTube-VOS 2018AVisT

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPMTrack-GAUC77.4—Unverified
2SPMTrack-LAUC76.8—Unverified
3MCITrack-L384AUC76.6—Unverified
4LoRAT-g-378AUC76.2—Unverified
5MCITrack-B224AUC75.3—Unverified
6DAM4SAMAUC75.1—Unverified
7LoRAT-L-378AUC75.1—Unverified
8SPMTrack-BAUC74.9—Unverified
9RTracker-LAUC74.7—Unverified
10SAMURAI-LAUC74.2—Unverified
#ModelMetricClaimedVerifiedStatus
1SAMURAI-LAverage Overlap81.7—Unverified
2DAM4SAMAverage Overlap81.1—Unverified
3SPMTrack-GAverage Overlap81—Unverified
4MITSAverage Overlap80.4—Unverified
5MCITrack-L384Average Overlap80—Unverified
6SPMTrack-LAverage Overlap80—Unverified
7ARTrackV2-LAverage Overlap79.5—Unverified
8LoRAT-g-378Average Overlap78.9—Unverified
9ARTrack-LAverage Overlap78.5—Unverified
10ODTrack-LAverage Overlap78.2—Unverified
#ModelMetricClaimedVerifiedStatus
1DropTrackNormalized Precision88.9—Unverified
2MCITrack-L384Accuracy87.9—Unverified
3SPMTrack-GAccuracy87.3—Unverified
4SPMTrack-LAccuracy86.9—Unverified
5MCITrack-B224Accuracy86.3—Unverified
6ARTrackV2-LAccuracy86.1—Unverified
7MixViT-L(ConvMAE)Accuracy86.1—Unverified
8SPMTrack-BAccuracy86.1—Unverified
9ODTrack-LAccuracy86.1—Unverified
10LoRAT-g-378Accuracy86—Unverified
#ModelMetricClaimedVerifiedStatus
1SAMURAI-LAUC61—Unverified
2DAM4SAMAUC60.9—Unverified
3LoRAT-L-378AUC56.6—Unverified
4LoRAT-g-378AUC56.5—Unverified
5UNINEXT-HAUC56.2—Unverified
6MCITrack-L384AUC55.7—Unverified
7RTracker-LAUC54.9—Unverified
8MCITrack-B224AUC54.6—Unverified
9ODTrack-LAUC53.9—Unverified
10ARTrackV2-LAUC53.4—Unverified
#ModelMetricClaimedVerifiedStatus
1GradNetPrecision0.86—Unverified
2SPMTrack-BAUC0.73—Unverified
3ODTrack-LAUC0.72—Unverified
4ODTrack-BAUC0.72—Unverified
5STMTrackAUC0.72—Unverified
6SAMURAI-LAUC0.72—Unverified
7PiVOT-LAUC0.71—Unverified
8HIPTrackAUC0.71—Unverified
9KeepTrackAUC0.71—Unverified
10TRASFUSTAUC0.7—Unverified
#ModelMetricClaimedVerifiedStatus
1LoRAT-g-378AUC0.74—Unverified
2LoRAT-L-378AUC0.73—Unverified
3NeighborTrack-OSTrackAUC0.73—Unverified
4SPMTrack-BAUC0.72—Unverified
5ARTrackV2-LAUC0.72—Unverified
6ARTrack-LAUC0.71—Unverified
7OSTrack -384AUC0.71—Unverified
8AiATrackAUC0.71—Unverified
9HIPTrackAUC0.71—Unverified
10MixFormerAUC0.7—Unverified
#ModelMetricClaimedVerifiedStatus
1MCITrack-L384AUC65.3—Unverified
2SPMTrack-GAUC64.7—Unverified
3SPMTrack-LAUC63.7—Unverified
4MCITrack-B224AUC62.9—Unverified
5LoRAT-g-378AUC62.7—Unverified
6LoRAT-L-378AUC62.3—Unverified
7SPMTrack-BAUC62—Unverified
8ODTrack-LAUC61.7—Unverified
9ARTrackV2-LAUC61.6—Unverified
10ODTrack-BAUC60.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SiamMask_EExpected Average Overlap (EAO)0.45—Unverified
2SiamFC++Expected Average Overlap (EAO)0.43—Unverified
3SiamRPN++_RExpected Average Overlap (EAO)0.42—Unverified
4THOR-SiamRPNExpected Average Overlap (EAO)0.42—Unverified
5SiamRPN++Expected Average Overlap (EAO)0.41—Unverified
6THOR-SiamMaskExpected Average Overlap (EAO)0.41—Unverified