Multi Object Tracking On Mot16

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MOTA

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			Paper Title
PPTracking	-	77.7	PP-YOLOE: An evolved version of YOLO
ReMOT	-	76.9	ReMOTS: Self-Supervised Refining Multi-Object Tracking and Segmentation
SGT	73.5	76.8	Detection Recovery in Online Multi-Object Tracking with Sparse Graph Tracker
STGT	76.8	76.7	TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking
FairMOT	-	74.9	FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
UniTrack	71.8	74.7	Do Different Tracking Tasks Require Different Appearance Models?
OUTrack_fm	71.1	74.2	Online Multi-Object Tracking with Unsupervised Re-Identification Learning and Occlusion Estimation
LMOT	72.3	73.2	LMOT: Efficient Light-Weight Detection and Tracking in Crowds
TraDeS	64.7	70.1	Track to Detect and Segment: An Online Multi-Object Tracker
QDTrack	67.1	69.8	Quasi-Dense Similarity Learning for Multiple Object Tracking
DEFT	-	68.03	DEFT: Detection Embeddings for Tracking
MOTR	67.0	66.8	MOTR: End-to-End Multiple-Object Tracking with Transformer
GSDT	-	66.7	Joint Object Detection and Multi-Object Tracking with Graph Neural Networks
JDE	-	64.4	Towards Real-Time Multi-Object Tracking
HopTrack[Embedded GPU]	-	63.12	HopTrack: A Real-time Multi-Object Tracking System for Embedded Devices
Lif_T	64.7	61.3	Lifted Disjoint Paths with Application in Multiple Object Tracking
MPNTrack	61.7	58.6	Learning a Neural Solver for Multiple Object Tracking
DeepMOT-Tracktor	-	54.8	How To Train Your Deep Multi-Object Tracker
MOTDT	-	50.9	Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification
TNT	-	49.2	Exploit the Connectivity: Multi-Object Tracking with TrackletNet

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Multi Object Tracking On Mot16

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