The KITTI Vision Benchmark Suite

we introduce faraway-frustum: a novel fusion
strategy for detecting faraway objects. The
main strategy is to depend solely on the 2D
vision for recognizing object class, as
object shape does not change drastically with
an increase in depth, and use pointcloud data
for object localization in the 3D space for
faraway objects. For closer objects, we use
learned pointcloud representations instead,
following state-of-the-art.

Distance threshold for faraway pedestrians:
60 meters
Distance threshold for faraway cars: 75
meters

@inproceedings{zhang2021faraway,
title={Faraway-frustum: Dealing with lidar sparsity for 3D object detection using fusion},
author={Zhang, Haolin and Yang, Dongfang and Yurtsever, Ekim and Redmill, Keith A and Ozguner, Umit},
booktitle={2021 IEEE International Intelligent Transportation Systems Conference (ITSC)},
pages={2646--2652},
year={2021},
organization={IEEE}
}