The KITTI Vision Benchmark Suite

JRMOT is a novel 3D MOT system that integrates
information from 2D RGB images and 3D point
clouds into a real-time performing framework.
Our system leverages advancements in neural-
network based reidentification as well as 2D and
3D detection and descriptors. We incorporate
this into a joint probabilistic data-association
framework within a multi-modal recursive Kalman
architecture to achieve online, real-time 3D
MOT.

See paper.

@inproceedings{Shenoi2020JRMOTAR,
title = {JRMOT: A Real-Time 3D Multi-Object
Tracker and a New Large-Scale Dataset},
author = {Abhijeet Shenoi and Mihir Patel and
JunYoung Gwak and Patrick Goebel and Amir
Sadeghian and Hamid Rezatofighi and Roberto
Mart{\'i}n-Mart{\'i}n and Silvio Savarese},
year = {2020},
booktitle = {The {IEEE/RSJ} International
Conference on Intelligent Robots and Systems
({IROS})},
url={https://arxiv.org/abs/2002.08397}
}