The KITTI Vision Benchmark Suite

A simple real-time 3D tracking pipeline built using standard components:

During each frame, independent detections from 3D and 2D are fused together into individual object instances. These instances are matched to existing tracks during two consecutive stages: first using 3D information (3D bounding box IoU) and then using 2D information (2D bounding box IoU).

The method is suitable for 3D Multi-Object Tracking and requires only bounding box level detections. To adjust the method for MOTS, mask information is used for more precise fusion.

Using segmentation masks from MOTSFusion

@inproceedings{Kim21ICRA,
title = {EagerMOT: 3D Multi-Object Tracking via Sensor Fusion},
author = {Kim, Aleksandr and Osep, Aljo\v{s}a and Leal-Taix{'e}, Laura},
booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
year = {2021}
}