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플랫폼
홈
SOTA
다중 객체 추적
Multi Object Tracking On Dancetrack
Multi Object Tracking On Dancetrack
평가 지표
AssA
HOTA
IDF1
MOTA
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
AssA
HOTA
IDF1
MOTA
Paper Title
MOTIP (Deformable DETR, with DanceTrack val and CrowdHuman)
65.9
73.7
78.4
92.7
Multiple Object Tracking as ID Prediction
MOTRv2
64.4
73.4
76.0
92.1
MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors
MOTIP (Deformable DETR, with CrowdHuman)
62.8
71.4
76.3
91.6
Multiple Object Tracking as ID Prediction
MOTIP (DAB-Deformable DETR)
60.8
70.0
75.1
91.0
Multiple Object Tracking as ID Prediction
CO-MOT
58.9
69.4
71.9
91.2
Bridging the Gap Between End-to-end and Non-End-to-end Multi-Object Tracking
MeMOTR
58.4
68.5
71.2
89.9
MeMOTR: Long-Term Memory-Augmented Transformer for Multi-Object Tracking
MOTIP (Deformable DETR)
57.6
67.5
72.2
90.3
Multiple Object Tracking as ID Prediction
MT_IOT
52.95
66.66
70.6
93.97
Multiple Object Tracking Challenge Technical Report for Team MT_IoT
AED
54.3
66.6
69.7
92.2
Associate Everything Detected: Facilitating Tracking-by-Detection to the Unknown
IMM-JHSE
55.41
66.24
71.72
89.95
One Homography is All You Need: IMM-based Joint Homography and Multiple Object State Estimation
Hybrid-SORT-ReID
52.6
65.7
67.4
91.8
Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking
UCMCTrack
-
63.6
65.0
-
UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation
MeMOTR (Deformable DETR)
52.3
63.4
65.5
85.4
MeMOTR: Long-Term Memory-Augmented Transformer for Multi-Object Tracking
DeepMoveSORT
48.6
63.0
65.0
92.6
Engineering an Efficient Object Tracker for Non-Linear Motion
Hybrid-SORT
47.4
62.2
63.0
91.6
Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking
C-TWiX
47.2
62.1
63.6
91.4
Learning Data Association for Multi-Object Tracking using Only Coordinates
CMTrack
46.4
61.8
63.3
92.5
A Confidence-Aware Matching Strategy For Generalized Multi-Object Tracking
Deep OC-SORT
45.8
61.3
61.5
92.3
Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification
C-BIoU
45.4
60.6
61.6
91.6
Hard to Track Objects with Irregular Motions and Similar Appearances? Make It Easier by Buffering the Matching Space
MotionTrack
41.7
58.2
58.6
91.3
MotionTrack: Learning Motion Predictor for Multiple Object Tracking
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