SOTAVerified

3D Object Tracking

3D Object Tracking is a computer vision task dedicated to monitoring and precisely locating objects as they navigate within a three-dimensional environment. It frequently utilizes 3D object detection techniques to pinpoint the objects and establish unique identifications that persist across multiple frames.

Papers

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Showing 1–50 of 67 papers

TitleStatusHype
FoundationPose: Unified 6D Pose Estimation and Tracking of Novel ObjectsCode4
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown ObjectsCode3
Panacea+: Panoramic and Controllable Video Generation for Autonomous DrivingCode3
TrackOcc: Camera-based 4D Panoptic Occupancy TrackingCode2
Center-based 3D Object Detection and TrackingCode2
CC-3DT: Panoramic 3D Object Tracking via Cross-Camera FusionCode2
You Only Demonstrate Once: Category-Level Manipulation from Single Visual DemonstrationCode2
Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object TrackingCode2
V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative PerceptionCode2
SceneTracker: Long-term Scene Flow Estimation NetworkCode2
Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless ObjectsCode2
RCooper: A Real-world Large-scale Dataset for Roadside Cooperative PerceptionCode2
Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose AnnotationsCode2
Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile DatasetCode1
3D Siamese Voxel-to-BEV Tracker for Sparse Point CloudsCode1
Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with TransformerCode1
GBOT: Graph-Based 3D Object Tracking for Augmented Reality-Assisted Assembly GuidanceCode1
BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D ModelsCode1
SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real WorldCode1
Large-displacement 3D Object Tracking with Hybrid Non-local OptimizationCode1
Monocular Quasi-Dense 3D Object TrackingCode1
CRN: Camera Radar Net for Accurate, Robust, Efficient 3D PerceptionCode1
RGB-D-E: Event Camera Calibration for Fast 6-DOF Object TrackingCode1
P2B: Point-to-Box Network for 3D Object Tracking in Point CloudsCode1
Prior-free 3D Object TrackingCode1
PTTR: Relational 3D Point Cloud Object Tracking with TransformerCode1
Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging StudiesCode1
Delving into Motion-Aware Matching for Monocular 3D Object TrackingCode1
TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory HypothesesCode1
Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking ApplicationsCode1
3D Object Tracking with TransformerCode1
Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data—0
3D-FCT: Simultaneous 3D Object Detection and Tracking Using Feature Correlation—0
BCOT: A Markerless High-Precision 3D Object Tracking Benchmark—0
BOTT: Box Only Transformer Tracker for 3D Object Tracking—0
CenterRadarNet: Joint 3D Object Detection and Tracking Framework using 4D FMCW Radar—0
CXTrack: Improving 3D Point Cloud Tracking with Contextual Information—0
DGD: Dynamic 3D Gaussians Distillation—0
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking—0
Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction—0
Estimating Metric Poses of Dynamic Objects Using Monocular Visual-Inertial Fusion—0
Evaluating the Robustness of LiDAR Point Cloud Tracking Against Adversarial Attack—0
Instant 3D Object Tracking with Applications in Augmented Reality—0
Joint Spatial-Temporal Optimization for Stereo 3D Object Tracking—0
Leveraging Temporal Cues for Semi-Supervised Multi-View 3D Object Detection—0
MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation—0
Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles—0
Robust Real-Time Tracking of Multiple Objects by Volumetric Mass Densities—0
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving—0
SpOT: Spatiotemporal Modeling for 3D Object Tracking—0
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All datasetsArgoverse CVPR 2020RTB

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Benson-RAVG-RANK99,999—Unverified
2pyDort_v1_rnet18_cv_cv_pedestrian_incAVG-RANK99,999—Unverified
3kevinsagen47AVG-RANK99,999—Unverified
4test_1AVG-RANK99,999—Unverified
5yk_yuanAVG-RANK99,999—Unverified
6maxage15-minhits5-conf0.3-thr0.01AVG-RANK99,999—Unverified
7kitty cov id = 1AVG-RANK99,999—Unverified
8EdwardAVG-RANK99,999—Unverified
9submit1AVG-RANK99,999—Unverified
10submit02AVG-RANK99,999—Unverified
#ModelMetricClaimedVerifiedStatus
1Mb-ICGADDS AUC91.1—Unverified