3D Multi-Object Tracking

32 papers with code • 6 benchmarks • 7 datasets

Image: Weng et al

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.

Probabilistic 3D Multi-Object Tracking for Autonomous Driving

eddyhkchiu/mahalanobis_3d_multi_object_tracking 16 Jan 2020

Our method estimates the object states by adopting a Kalman Filter.

EagerMOT: 3D Multi-Object Tracking via Sensor Fusion

aleksandrkim61/EagerMOT 29 Apr 2021

Multi-object tracking (MOT) enables mobile robots to perform well-informed motion planning and navigation by localizing surrounding objects in 3D space and time.

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving

qcraftai/simtrack ICCV 2021

3D multi-object tracking in LiDAR point clouds is a key ingredient for self-driving vehicles.

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.

SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking

tusimple/simpletrack 18 Nov 2021

3D multi-object tracking (MOT) has witnessed numerous novel benchmarks and approaches in recent years, especially those under the "tracking-by-detection" paradigm.

SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking

synsin0/srcn3d 29 Jun 2022

Our novel sparse feature sampling module only utilizes local 2D region of interest (RoI) features calculated by the projection of 3D query boxes for further box refinement, leading to a fully-convolutional and deployment-friendly pipeline.

Probabilistic 3D Multi-Object Cooperative Tracking for Autonomous Driving via Differentiable Multi-Sensor Kalman Filter

eddyhkchiu/DMSTrack 26 Sep 2023

However, their proposed methods mainly use cooperative detection results as input to a standard single-sensor Kalman Filter-based tracking algorithm.

FANTrack: 3D Multi-Object Tracking with Feature Association Network

wise-lab/fantrack 7 May 2019

Instead, we exploit the power of deep learning to formulate the data association problem as inference in a CNN.

3D Multi-Object Tracking: A Baseline and New Evaluation Metrics

xinshuoweng/AB3DMOT 9 Jul 2019

Additionally, 3D MOT datasets such as KITTI evaluate MOT methods in the 2D space and standardized 3D MOT evaluation tools are missing for a fair comparison of 3D MOT methods.