3D Multi-Object Tracking
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Benchmarks
nuScenes
nuscenes Camera-Radar
Waymo Open Dataset
nuScenes Camera Only
nuScenes LiDAR only
Most implemented
Simple Online and Realtime Tracking with a Deep Association Metric
Center-based 3D Object Detection and Tracking
Track Initialization and Re-Identification for~3D Multi-View Multi-Object Tracking
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving
EagerMOT: 3D Multi-Object Tracking via Sensor Fusion
Papers
Does Appearance Help? A Systematic Study of Image-Based Re-Identification in Online 3D Multi-Pedestrian Tracking
LiDAR-based 3D Multi-Object Tracking (MOT) typically relies solely on geometric information, which is often insufficient to distinguish between targets during prolonged occlusions or in crowded human-populated environmen…
3D Multi-Object TrackingWeakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimation
Due to the difficulty of obtaining ground-truth data for 4D radar scene flow estimation, previous methods typically rely on either self-supervised losses or cross-modal supervision using 3D LiDAR data, 2D images, and odo…
3D Multi-Object TrackingScene Flow EstimationPoint CloudsEfficient Online 3D Multi-Camera Multi-Object Tracking and Pose Estimation
This paper proposes a fast and online method for jointly performing 3D multi-object tracking and pose estimation using multiple monocular cameras. Our algorithm requires only 2D bounding box and pose detections, eliminat…
3D Multi-Object TrackingComputational EfficiencyPose EstimationRadar-Informed 3D Multi-Object Tracking under Adverse Conditions
The challenge of 3D multi-object tracking is achieving robustness in real-world applications, for example under adverse conditions and maintaining consistency as distance increases. To overcome these challenges, sensor f…
3D Multi-Object TrackingPoint CloudsS3KF: Spherical State-Space Kalman Filtering for Panoramic 3D Multi-Object Tracking
Panoramic multi-object tracking is important for industrial safety monitoring, wide-area robotic perception, and infrastructure-light deployment in large workspaces. In these settings, the sensing system must provide ful…
3D Multi-Object TrackingDepth EstimationFusion-Poly: A Polyhedral Framework Based on Spatial-Temporal Fusion for 3D Multi-Object Tracking
LiDAR-camera 3D multi-object tracking (MOT) combines rich visual semantics with accurate depth cues to improve trajectory consistency and tracking reliability. In practice, however, LiDAR and cameras operate at different…
3D Multi-Object Tracking