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 101–150 of 341 papers

TitleStatusHype
PatchNet -- Short-range Template Matching for Efficient Video ProcessingCode1
PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionCode1
Low-Light Object Tracking: A BenchmarkCode1
ProContEXT: Exploring Progressive Context Transformer for TrackingCode1
Revealing the Dark Secrets of Masked Image ModelingCode1
NT-VOT211: A Large-Scale Benchmark for Night-time Visual Object TrackingCode1
Multi-modal Visual Tracking: Review and Experimental ComparisonCode1
Ocean: Object-aware Anchor-free TrackingCode1
360VOT: A New Benchmark Dataset for Omnidirectional Visual Object TrackingCode1
Improving Visual Object Tracking through Visual PromptingCode1
HIPTrack: Visual Tracking with Historical PromptsCode1
Learning Spatio-Temporal Transformer for Visual TrackingCode1
RGBD1K: A Large-scale Dataset and Benchmark for RGB-D Object TrackingCode1
Cross-Drone Transformer Network for Robust Single Object TrackingCode1
Mamba-FETrack V2: Revisiting State Space Model for Frame-Event based Visual Object TrackingCode1
Siamese Object Tracking for Unmanned Aerial Vehicle: A Review and Comprehensive AnalysisCode1
Exploring Fusion Strategies for Accurate RGBT Visual Object TrackingCode1
Compact Transformer Tracker with Correlative Masked ModelingCode1
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual TrackingCode1
Continuity-Discrimination Convolutional Neural Network for Visual Object Tracking—0
Context-aware Visual Tracking with Joint Meta-updating—0
AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection—0
Adapting SAM 2 for Visual Object Tracking: 1st Place Solution for MMVPR Challenge Multi-Modal Tracking—0
A Novel Low-cost FPGA-based Real-time Object Tracking System—0
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks—0
Foreground-Background Distribution Modeling Transformer for Visual Object Tracking—0
Fast Integral Image Estimation at 1% measurement rate—0
Comparative Study of ECO and CFNet Trackers in Noisy Environment—0
An Exploration of Target-Conditioned Segmentation Methods for Visual Object Trackers—0
Exploring Dynamic Transformer for Efficient Object Tracking—0
CoCoLoT: Combining Complementary Trackers in Long-Term Visual Tracking—0
Exploring Causal Relationships in Visual Object Tracking—0
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model—0
An Experimental Survey on Correlation Filter-based Tracking—0
Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking—0
ACTrack: Adding Spatio-Temporal Condition for Visual Object Tracking—0
MITracker: Multi-View Integration for Visual Object Tracking—0
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking—0
EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events—0
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark—0
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark—0
Accurate Anchor Free Tracking—0
Enhancing Tracking Robustness with Auxiliary Adversarial Defense Networks—0
A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning—0
An Efficient 3D CNN for Action/Object Segmentation in Video—0
Learning to Update for Object Tracking with Recurrent Meta-learner—0
Leveraging the Power of Data Augmentation for Transformer-based Tracking—0
Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking—0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning—0
Learning Target Candidate Association to Keep Track of What Not to Track—0
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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
6ODTrack-LAccuracy86.1—Unverified
7ARTrackV2-LAccuracy86.1—Unverified
8SPMTrack-BAccuracy86.1—Unverified
9MixViT-L(ConvMAE)Accuracy86.1—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
2NeighborTrack-OSTrackAUC0.73—Unverified
3LoRAT-L-378AUC0.73—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