3D Multi Object Tracking On Waymo Open 1
المقاييس
MOTA/L2
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
اسم النموذج | MOTA/L2 | Paper Title | Repository |
|---|---|---|---|
| REIDMOT3D | 0.5961 | - | - |
| ImmortalTracker | 0.6055 | Immortal Tracker: Tracklet Never Dies | |
| Trajectoryformer | 0.6573 | - | - |
| OptMOT | 0.6218 | - | - |
| MFMS_Track | 0.6314 | - | - |
| RobMOT | 0.7466 | 0/1 Deep Neural Networks via Block Coordinate Descent | - |
| HorizonMOT3D | 0.6407 | - | - |
| InceptioLidar | 0.6558 | - | - |
| SimpleTrack | 0.6018 | SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking | |
| Fast-Poly | 0.6306 | - | - |
| CenterPoint | 0.5938 | - | - |
| CasTrack | 0.6366 | - | - |
| BTT | 0.5949 | - | - |
| CTRL_FSD_TTA | 0.7429 | FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels | |
| YONTD_MOT | 0.6048 | - | - |
| DRTracker | 0.6675 | - | - |
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