Multi Object Tracking On Mot17

Métriques

MOTA

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	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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