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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1826–1850 of 1966 papers

TitleStatusHype
Memory Maps for Video Object Detection and Tracking on UAVs—0
MeMOT: Multi-Object Tracking with Memory—0
MeNToS: Tracklets Association with a Space-Time Memory Network—0
Merging Tasks for Video Panoptic Segmentation—0
Mesh-SORT: Simple and effective location-wise tracker with lost management strategies—0
Metric Learning Driven Multi-Task Structured Output Optimization for Robust Keypoint Tracking—0
Metro-haul Project Vertical Service Demo: Video Surveillance Real-time Low-latency Object Tracking—0
MEVDT: Multi-Modal Event-Based Vehicle Detection and Tracking Dataset—0
MEX: Memory-efficient Approach to Referring Multi-Object Tracking—0
Middle Fusion and Multi-Stage, Multi-Form Prompts for Robust RGB-T Tracking—0
Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Tracking—0
MissFormer: (In-)attention-based handling of missing observations for trajectory filtering and prediction—0
MITracker: Multi-View Integration for Visual Object Tracking—0
Partial Binarization of Neural Networks for Budget-Aware Efficient Learning—0
Mixture of Dynamical Variational Autoencoders for Multi-Source Trajectory Modeling and Separation—0
Mixture of Pre-processing Experts Model for Noise Robust Deep Learning on Resource Constrained Platforms—0
MLS-Track: Multilevel Semantic Interaction in RMOT—0
MMPTRACK: Large-scale Densely Annotated Multi-camera Multiple People Tracking Benchmark—0
MOANA: An Online Learned Adaptive Appearance Model for Robust Multiple Object Tracking in 3D—0
Mobile Object Tracking in Panoramic Video and LiDAR for Radiological Source-Object Attribution and Improved Source Detection—0
Motion State: A New Benchmark Multiple Object Tracking—0
Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations—0
Model-free Tracking with Deep Appearance and Motion Features Integration—0
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking—0
Modeling Continuous Motion for 3D Point Cloud Object Tracking—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