SOTAVerified

Object Tracking

Object tracking is the task of taking an initial set of object detections, creating a unique ID for each of the initial detections, and then tracking each of the objects as they move around frames in a video, maintaining the ID assignment. State-of-the-art methods involve fusing data from RGB and event-based cameras to produce more reliable object tracking. CNN-based models using only RGB images as input are also effective. The most popular benchmark is OTB. There are several evaluation metrics specific to object tracking, including HOTA, MOTA, IDF1, and Track-mAP.

( Image credit: Towards-Realtime-MOT )

Papers

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Showing 951–975 of 1966 papers

TitleStatusHype
Lighter Stacked Hourglass Human Pose Estimation—0
InterTracker: Discovering and Tracking General Objects Interacting with Hands in the Wild—0
Deep-LK for Efficient Adaptive Object Tracking—0
Lightweight RGB-T Tracking with Mobile Vision Transformers—0
Interpretable Deep Tracking—0
InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling—0
Deep LG-Track: An Enhanced Localization-Confidence-Guided Multi-Object Tracker—0
Interactive Multi-scale Fusion of 2D and 3D Features for Multi-object Tracking—0
Interactive Instance Annotation with Siamese Networks—0
Deep Learning Techniques for Video Instance Segmentation: A Survey—0
Interaction-Aware Labeled Multi-Bernoulli Filter—0
Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video—0
Deep Learning of Appearance Models for Online Object Tracking—0
Local Subspace Collaborative Tracking—0
Long Range Object-Level Monocular Depth Estimation for UAVs—0
Long Short-Term Memory Kalman Filters:Recurrent Neural Estimators for Pose Regularization—0
Background subtraction on depth videos with convolutional neural networks—0
Intelligent driving vehicle front multi-target tracking and detection based on YOLOv5 and point cloud 3D projection—0
Long-term Tracking in the Wild: A Benchmark—0
Integration of Regularized l1 Tracking and Instance Segmentation for Video Object Tracking—0
Deep Learning Method for Cell-Wise Object Tracking, Velocity Estimation and Projection of Sensor Data over Time—0
Integration of the 3D Environment for UAV Onboard Visual Object Tracking—0
Integrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning—0
Deep Learning in Video Multi-Object Tracking: A Survey—0
BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos—0
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All datasetsCOESOTFE108QuadTrackSeaDronesSeeBIRDSAI - ICVGIP 2020KITTIMMPTRACKPerception TestVisEvent

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HR-CEUTrack-LargeSuccess Rate65—Unverified
2HR-CEUTrack-BaseSuccess Rate63.2—Unverified
3CEUTrack-LargeSuccess Rate62.8—Unverified
4CEUTrack-BaseSuccess Rate62—Unverified
5SiamR-CNNSuccess Rate60.9—Unverified
6TransTSuccess Rate60.5—Unverified
7SuperDiMPSuccess Rate60.2—Unverified
8TrDiMPSuccess Rate60.1—Unverified
9KeepTrackSuccess Rate59.6—Unverified
10AiATrackSuccess Rate59—Unverified
#ModelMetricClaimedVerifiedStatus
1HR-MonTrack-BaseSuccess Rate68.5—Unverified
2HR-MonTrack-TinySuccess Rate66.3—Unverified
3Multi-modalSuccess Rate63.4—Unverified
4PrDiMPSuccess Rate59—Unverified
5DiMPSuccess Rate57.1—Unverified
6MonTrackSuccess Rate54.9—Unverified
7ATOMSuccess Rate46.5—Unverified
8KYSSuccess Rate26.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniTrackHOTA23.45—Unverified
2DeepSORTHOTA21.16—Unverified
3OC-SORTHOTA20.83—Unverified
4ByteTrackHOTA20.66—Unverified
5TrackFormerHOTA19.62—Unverified
6HybridSORTHOTA16.64—Unverified
7DiffMOTHOTA16.4—Unverified
8Bot-SORTHOTA15.77—Unverified
#ModelMetricClaimedVerifiedStatus
1DiMP50Success Rate67.33—Unverified
2PrDiMP50Success Rate67—Unverified
3PrDiMP18Success Rate65.9—Unverified
4DiMP18Success Rate64.6—Unverified
5AtomSuccess Rate63.8—Unverified
#ModelMetricClaimedVerifiedStatus
1finalHumans0.14—Unverified
2night_furyHumans0.05—Unverified
3Yolo based methodHumans0.02—Unverified
4finalHumans0—Unverified
#ModelMetricClaimedVerifiedStatus
1M2-Trackmean precision83.4—Unverified
2BATmean precision75.2—Unverified
#ModelMetricClaimedVerifiedStatus
1UMMT3DMOTA95—Unverified
2MMPTRACK3DMOTA94.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Siam-FCAverage IOU0.66—Unverified
#ModelMetricClaimedVerifiedStatus
1RT-MDNetPrecision Plot0.63—Unverified