Multi Object Tracking On Mot17

Metriken

MOTA

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	MOTA	Paper Title	Repository
JBNOT	52.6	Multiple People Tracking using Body and Joint Detections	-
SparseTrack	81.0	SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depth
StrongSORT	79.6	StrongSORT: Make DeepSORT Great Again
Fast-StrongSORT	-	When to Extract ReID Features: A Selective Approach for Improved Multiple Object Tracking
DEFT	66.6	DEFT: Detection Embeddings for Tracking
Unicorn	77.2	Towards Grand Unification of Object Tracking
CenterTrack + TrajE	67.8	Multiple Object Tracking with Mixture Density Networks for Trajectory Estimation	-
CMTrack	80.7	A Confidence-Aware Matching Strategy For Generalized Multi-Object Tracking
BoostTrack+	80.6	BoostTrack: boosting the similarity measure and detection confidence for improved multiple object tracking
STGT	76.7	TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking	-
Deep OC-SORT	79.4	Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification
TraDeS	69.1	Track to Detect and Segment: An Online Multi-Object Tracker	-
BoT-SORT	80.5	BoT-SORT: Robust Associations Multi-Pedestrian Tracking
C-TWiX	78.1	Learning Data Association for Multi-Object Tracking using Only Coordinates
GTR	75.3	Global Tracking Transformers
QDTrack	68.7	Quasi-Dense Similarity Learning for Multiple Object Tracking
IMM-JHSE	79.54	One Homography is All You Need: IMM-based Joint Homography and Multiple Object State Estimation
DeepMOT-Tracktor	53.7	How To Train Your Deep Multi-Object Tracker
TrackFormer	74.1	TrackFormer: Multi-Object Tracking with Transformers
MOTR	67.4	MOTR: End-to-End Multiple-Object Tracking with Transformer

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