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 201225 of 341 papers

TitleStatusHype
Is First Person Vision Challenging for Object Tracking?0
Learning Consistency Pursued Correlation Filters for Real-Time UAV Tracking0
Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking0
Learning Dynamic Siamese Network for Visual Object Tracking0
Learning feed-forward one-shot learners0
Learning Global Structure Consistency for Robust Object Tracking0
Learning Hierarchical Features for Visual Object Tracking with Recursive Neural Networks0
Learning Mobile CNN Feature Extraction Toward Fast Computation of Visual Object Tracking0
Learning Policies for Adaptive Tracking with Deep Feature Cascades0
Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking0
Learning Spatial Distribution of Long-Term Trackers Scores0
Learning Target Candidate Association to Keep Track of What Not to Track0
Learning to Update for Object Tracking with Recurrent Meta-learner0
Leveraging the Power of Data Augmentation for Transformer-based Tracking0
MITracker: Multi-View Integration for Visual Object Tracking0
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking0
Motion Prediction in Visual Object Tracking0
Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking0
Multi-modal Tracking for Object based SLAM0
Multiple Feature Fusion via Weighted Entropy for Visual Tracking0
Multiple-Vehicle Tracking in the Highway Using Appearance Model and Visual Object Tracking0
Improving Siamese Based Trackers with Light or No Training through Multiple Templates and Temporal Network0
Network Comparison Study of Deep Activation Feature Discriminability with Novel Objects0
Object Tracking based on Quantum Particle Swarm Optimization0
Object Tracking through Residual and Dense LSTMs0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPMTrack-GAUC77.4Unverified
2SPMTrack-LAUC76.8Unverified
3MCITrack-L384AUC76.6Unverified
4LoRAT-g-378AUC76.2Unverified
5MCITrack-B224AUC75.3Unverified
6DAM4SAMAUC75.1Unverified
7LoRAT-L-378AUC75.1Unverified
8SPMTrack-BAUC74.9Unverified
9RTracker-LAUC74.7Unverified
10SAMURAI-LAUC74.2Unverified
#ModelMetricClaimedVerifiedStatus
1SAMURAI-LAverage Overlap81.7Unverified
2DAM4SAMAverage Overlap81.1Unverified
3SPMTrack-GAverage Overlap81Unverified
4MITSAverage Overlap80.4Unverified
5MCITrack-L384Average Overlap80Unverified
6SPMTrack-LAverage Overlap80Unverified
7ARTrackV2-LAverage Overlap79.5Unverified
8LoRAT-g-378Average Overlap78.9Unverified
9ARTrack-LAverage Overlap78.5Unverified
10ODTrack-LAverage Overlap78.2Unverified
#ModelMetricClaimedVerifiedStatus
1DropTrackNormalized Precision88.9Unverified
2MCITrack-L384Accuracy87.9Unverified
3SPMTrack-GAccuracy87.3Unverified
4SPMTrack-LAccuracy86.9Unverified
5MCITrack-B224Accuracy86.3Unverified
6ODTrack-LAccuracy86.1Unverified
7ARTrackV2-LAccuracy86.1Unverified
8SPMTrack-BAccuracy86.1Unverified
9MixViT-L(ConvMAE)Accuracy86.1Unverified
10LoRAT-g-378Accuracy86Unverified
#ModelMetricClaimedVerifiedStatus
1SAMURAI-LAUC61Unverified
2DAM4SAMAUC60.9Unverified
3LoRAT-L-378AUC56.6Unverified
4LoRAT-g-378AUC56.5Unverified
5UNINEXT-HAUC56.2Unverified
6MCITrack-L384AUC55.7Unverified
7RTracker-LAUC54.9Unverified
8MCITrack-B224AUC54.6Unverified
9ODTrack-LAUC53.9Unverified
10ARTrackV2-LAUC53.4Unverified
#ModelMetricClaimedVerifiedStatus
1GradNetPrecision0.86Unverified
2SPMTrack-BAUC0.73Unverified
3ODTrack-LAUC0.72Unverified
4ODTrack-BAUC0.72Unverified
5STMTrackAUC0.72Unverified
6SAMURAI-LAUC0.72Unverified
7PiVOT-LAUC0.71Unverified
8HIPTrackAUC0.71Unverified
9KeepTrackAUC0.71Unverified
10TRASFUSTAUC0.7Unverified
#ModelMetricClaimedVerifiedStatus
1LoRAT-g-378AUC0.74Unverified
2NeighborTrack-OSTrackAUC0.73Unverified
3LoRAT-L-378AUC0.73Unverified
4SPMTrack-BAUC0.72Unverified
5ARTrackV2-LAUC0.72Unverified
6ARTrack-LAUC0.71Unverified
7OSTrack -384AUC0.71Unverified
8AiATrackAUC0.71Unverified
9HIPTrackAUC0.71Unverified
10MixFormerAUC0.7Unverified
#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
#ModelMetricClaimedVerifiedStatus
1SiamMask_EExpected Average Overlap (EAO)0.45Unverified
2SiamFC++Expected Average Overlap (EAO)0.43Unverified
3SiamRPN++_RExpected Average Overlap (EAO)0.42Unverified
4THOR-SiamRPNExpected Average Overlap (EAO)0.42Unverified
5SiamRPN++Expected Average Overlap (EAO)0.41Unverified
6THOR-SiamMaskExpected Average Overlap (EAO)0.41Unverified