# 3D-FCT: Simultaneous 3D Object Detection and Tracking Using Feature Correlation

Source: [3D-FCT: Simultaneous 3D Object Detection and Tracking Using Feature Correlation](<https://www.sota2.com/research/paper/68fa6aee1e209131cea2b245>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-04T03:35:52.585Z

Authors: Naman Sharma, Hocksoon Lim

Published: 2021-10-06T06:36:29.000Z

## Abstract

3D object detection using LiDAR data remains a key task for applications like autonomous driving and robotics. Unlike in the case of 2D images, LiDAR data is almost always collected over a period of time. However, most work in this area has focused on performing detection independent of the temporal domain. In this paper we present 3D-FCT, a Siamese network architecture that utilizes temporal information to simultaneously perform the related tasks of 3D object detection and tracking. The network is trained to predict the movement of an object based on the correlation features of extracted keypoints across time. Calculating correlation across keypoints only allows for real-time object detection. We further extend the multi-task objective to include a tracking regression loss. Finally, we produce high accuracy detections by linking short-term object tracklets into long term tracks based on the predicted tracks. Our proposed method is evaluated on the KITTI tracking dataset where it is shown to provide an improvement of 5.57% mAP over a state-of-the-art approach.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [3D Object Detection on KITTI tracking Easy (val)](<https://www.sota2.com/research/sota/3d-object-detection-on-kitti-tracking-easy-val.md>): 3D Object Detection; KITTI tracking Easy (val); AP (Car): 89.56.

- [3D Object Detection on KITTI tracking Hard (val)](<https://www.sota2.com/research/sota/3d-object-detection-on-kitti-tracking-hard-val.md>): 3D Object Detection; KITTI tracking Hard (val); AP (Car): 72.72.

- [3D Object Detection on KITTI tracking Medium (val)](<https://www.sota2.com/research/sota/3d-object-detection-on-kitti-tracking-medium-val.md>): 3D Object Detection; KITTI tracking Medium (val); AP (Car): 0.7207.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2110.02531>)

[PDF](<https://arxiv.org/pdf/2110.02531.pdf>)