Multiple Object Tracking On Kitti Test Online

Métriques

HOTA

IDSW

MOTA

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	HOTA	IDSW	MOTA	Paper Title	Repository
IMM-JHSE	79.21	177	89.8	One Homography is All You Need: IMM-based Joint Homography and Multiple Object State Estimation	-
EagerMOT	74.39	239	87.82	EagerMOT: 3D Multi-Object Tracking via Sensor Fusion	-
mmMOT	62.05	-	84.77	Robust Multi-Modality Multi-Object Tracking	-
KFDL	81.06	22	90.29	-	-
LEGO	80.75	214	90.61	LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Clouds	-
NOMT	-	-	78.15	Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor	-
QD-3DT	72.77	-	86.41	Monocular Quasi-Dense 3D Object Tracking	-
PMBM	-	-	80.39	Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering	-
JRMOT	69.61	-	85.70	JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset	-
mmMOT-normal	-	-	84.77	Robust Multi-Modality Multi-Object Tracking	-
CenterTrack	73.02	-	89.44	Tracking Objects as Points	-
MDP	-	-	76.59	Learning to Track: Online Multi-Object Tracking by Decision Making	-
CIWT	-	-	75.39	Combined Image- and World-Space Tracking in Traffic Scenes	-
MCTrack	81.07	64	89.82	MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving	-
UCMCTrack	77.1	-	90.4	UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation	-
NOMT-HM	-	-	75.20	Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor	-
PC-TCNN	80.90	37	78.46	-	-
SRK ODESA	-	-	90.03	Learning Local Feature Descriptors for Multiple Object Tracking	-
SCEA	-	-	75.58	Online Multi-Object Tracking via Structural Constraint Event Aggregation	-
DSM	-	-	76.15	End-to-end Learning of Multi-sensor 3D Tracking by Detection	-

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