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 151–200 of 341 papers

TitleStatusHype
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation—0
Benchmarking Deep Trackers on Aerial Videos—0
Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking—0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning—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
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model—0
CoCoLoT: Combining Complementary Trackers in Long-Term Visual Tracking—0
Comparative Study of ECO and CFNet Trackers in Noisy Environment—0
Context-aware Visual Tracking with Joint Meta-updating—0
Continuity-Discrimination Convolutional Neural Network for Visual Object Tracking—0
Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency—0
Convolutional Regression for Visual Tracking—0
Correlation filter tracking with adaptive proposal selection for accurate scale estimation—0
D3S - A Discriminative Single Shot Segmentation Tracker—0
DeepMix: Online Auto Data Augmentation for Robust Visual Object Tracking—0
Deep Reinforcement Learning for Visual Object Tracking in Videos—0
Dense Optical Flow Estimation Using Sparse Regularizers from Reduced Measurements—0
Depth-only Object Tracking—0
DeTrack: In-model Latent Denoising Learning for Visual Object Tracking—0
DIMBA: Discretely Masked Black-Box Attack in Single Object Tracking—0
Discriminative Scale Space Tracking—0
Discussion among Different Methods of Updating Model Filter in Object Tracking—0
Distractor-aware Event-based Tracking—0
DMV: Visual Object Tracking via Part-level Dense Memory and Voting-based Retrieval—0
DreamTrack: Dreaming the Future for Multimodal Visual Object Tracking—0
Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking—0
Efficient Adversarial Attacks for Visual Object Tracking—0
Efficient Counterfactual Learning from Bandit Feedback—0
Efficient Training for Visual Tracking with Deformable Transformer—0
Efficient universal shuffle attack for visual object tracking—0
Enhancing Tracking Robustness with Auxiliary Adversarial Defense Networks—0
EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events—0
Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking—0
Exploring Causal Relationships in Visual Object Tracking—0
Exploring Dynamic Transformer for Efficient Object Tracking—0
Fast Integral Image Estimation at 1% measurement rate—0
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks—0
Foreground-Background Distribution Modeling Transformer for Visual Object Tracking—0
Fully Spiking Neural Networks for Unified Frame-Event Object Tracking—0
General Compression Framework for Efficient Transformer Object Tracking—0
Handcrafted and Deep Trackers: Recent Visual Object Tracking Approaches and Trends—0
Hard Occlusions in Visual Object Tracking—0
Heteroskedastic Geospatial Tracking with Distributed Camera Networks—0
Hierarchical Convolutional Features for Visual Tracking—0
Higher Performance Visual Tracking with Dual-Modal Localization—0
High Performance Visual Object Tracking with Unified Convolutional Networks—0
Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach—0
Instance-Level Video Segmentation From Object Tracks—0
Integration of the 3D Environment for UAV Onboard Visual 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