3D Object Tracking
33 papers with code • 2 benchmarks • 11 datasets
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.
Benchmarks
These leaderboards are used to track progress in 3D Object Tracking
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Libraries
Use these libraries to find 3D Object Tracking models and implementationsDatasets
KITTI
Argoverse
K-Radar
MOTFront
TrackML challenge Throughput phase dataset
IBISCape
DTTD
3D-POP
RTB
Most implemented papers
Center-based 3D Object Detection and Tracking
tianweiy/CenterPoint
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CVPR 2021
Three-dimensional objects are commonly represented as 3D boxes in a point-cloud.
Argoverse: 3D Tracking and Forecasting with Rich Maps
In our baseline experiments, we illustrate how detailed map information such as lane direction, driveable area, and ground height improves the accuracy of 3D object tracking and motion forecasting.
Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applications
augcog/dttdv1
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Digital twin is a problem of augmenting real objects with their digital counterparts.
Robust Digital-Twin Localization via An RGBD-based Transformer Network and A Comprehensive Evaluation on a Mobile Dataset
augcog/dttd2
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The potential of digital-twin technology, involving the creation of precise digital replicas of physical objects, to reshape AR experiences in 3D object tracking and localization scenarios is significant.
P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds
Specifically, we first sample seeds from the point clouds in template and search area respectively.
SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World
Finally, we use a pre-rendered sparse viewpoint model to create a joint posterior probability for the object pose.
You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration
The canonical object representation is learned solely in simulation and then used to parse a category-level, task trajectory from a single demonstration video.
Uncertainty-Aware AB3DMOT by Variational 3D Object Detection
Autonomous driving needs to rely on high-quality 3D object detection to ensure safe navigation in the world.
Variational Voxel Pseudo Image Tracking
Uncertainty estimation is an important task for critical problems, such as robotics and autonomous driving, because it allows creating statistically better perception models and signaling the model's certainty in its predictions to the decision method or a human supervisor.
Dynamics Based 3D Skeletal Hand Tracking
melax/hand_tracking_samples
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Based on a depth sensor's samples, the system generates constraints that limit motion orthogonal to the rigid body model's surface.
