3D Object Tracking

31 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.


Use these libraries to find 3D Object Tracking models and implementations

Most implemented papers

Center-based 3D Object Detection and Tracking

tianweiy/CenterPoint CVPR 2021

Three-dimensional objects are commonly represented as 3D boxes in a point-cloud.

Argoverse: 3D Tracking and Forecasting with Rich Maps

argoai/argoverse-api CVPR 2019

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 12 Feb 2023

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 24 Sep 2023

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

HaozheQi/P2B CVPR 2020

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

dlr-rm/3dobjecttracking 25 Oct 2021

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

wenbowen123/catgrasp 30 Jan 2022

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

opendr/variational-voxel-3d-detetction 12 Feb 2023

Autonomous driving needs to rely on high-quality 3D object detection to ensure safe navigation in the world.

Variational Voxel Pseudo Image Tracking

opendr/variational-voxel-3d-detetction 12 Feb 2023

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 22 May 2017

Based on a depth sensor's samples, the system generates constraints that limit motion orthogonal to the rigid body model's surface.