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 251–300 of 341 papers

TitleStatusHype
ACTrack: Adding Spatio-Temporal Condition for Visual Object Tracking—0
Accurate Anchor Free Tracking—0
Depth-only Object Tracking—0
RTrack: Accelerating Convergence for Visual Object Tracking via Pseudo-Boxes Exploration—0
Dense Optical Flow Estimation Using Sparse Regularizers from Reduced Measurements—0
Saliency-Enhanced Robust Visual Tracking—0
Deep Reinforcement Learning for Visual Object Tracking in Videos—0
DeepMix: Online Auto Data Augmentation for Robust Visual Object Tracking—0
D3S - A Discriminative Single Shot Segmentation Tracker—0
Correlation filter tracking with adaptive proposal selection for accurate scale estimation—0
A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning—0
Convolutional Regression for Visual Tracking—0
360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos—0
Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency—0
Continuity-Discrimination Convolutional Neural Network for Visual Object Tracking—0
Context-aware Visual Tracking with Joint Meta-updating—0
Comparative Study of ECO and CFNet Trackers in Noisy Environment—0
DomainSiam: Domain-Aware Siamese Network for Visual Object Tracking—0
CoCoLoT: Combining Complementary Trackers in Long-Term Visual Tracking—0
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model—0
Video Propagation Networks—0
SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking—0
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark—0
SiamSNN: Siamese Spiking Neural Networks for Energy-Efficient Object Tracking—0
SiamTHN: Siamese Target Highlight Network for Visual Tracking—0
Video Tracking Using Learned Hierarchical Features—0
Single Object Tracking Research: A Survey—0
Visual Object Tracking across Diverse Data Modalities: A Review—0
Visual Object Tracking based on Adaptive Siamese and Motion Estimation Network—0
Visual Object Tracking by Segmentation with Graph Convolutional Network—0
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark—0
Spectral Filter Tracking—0
SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking—0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning—0
SRRT: Exploring Search Region Regulation for Visual Object Tracking—0
Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking—0
Benchmarking Deep Trackers on Aerial Videos—0
Visual Object Tracking in First Person Vision—0
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation—0
BASE: Probably a Better Approach to Multi-Object Tracking—0
BackTrack: Robust template update via Backward Tracking of candidate template—0
Autoregressive Sequential Pretraining for Visual Tracking—0
Visual Object Tracking on Multi-modal RGB-D Videos: A Review—0
Real-time Visual Object Tracking with Natural Language Description—0
Autoregressive Queries for Adaptive Tracking with Spatio-TemporalTransformers—0
Temporally-Transferable Perturbations: Efficient, One-Shot Adversarial Attacks for Online Visual Object Trackers—0
Visual object tracking performance measures revisited—0
Towards a Better Match in Siamese Network Based Visual Object Tracker—0
Towards Efficient Training with Negative Samples in Visual Tracking—0
AttTrack: Online Deep Attention Transfer for Multi-object Tracking—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