Method

An Efficient Probabilistic 3D Object Detector for Autonomous Driving [LaserNet]


Submitted on 24 Mar. 2019 15:40 by
Ankit Laddha (Uber ATG)

Running time:12 ms
Environment:GPU @ 2.5 Ghz (C/C++)

Method Description:
See paper for details
Parameters:
See paper for details
Latex Bibtex:
@inproceedings{lasernet,
title={{LaserNet}: An Efficient Probabilistic 3{D} Object
Detector for Autonomous Driving},
author={Meyer, Gregory P. and Laddha, Ankit and Kee, Eric
and Vallespi-Gonzalez, Carlos and Wellington, Carl K.},
booktitle={Proceedings of the IEEE Conference on
Computer Vision and Pattern Recognition (CVPR)},
year={2019}
}

Detailed Results

Object detection and orientation estimation results. Results for object detection are given in terms of average precision (AP) and results for joint object detection and orientation estimation are provided in terms of average orientation similarity (AOS).


Benchmark Easy Moderate Hard
Car (Detection) 0.00 % 0.00 % 0.00 %
Car (Bird's Eye View) 78.25 % 73.77 % 66.47 %
This table as LaTeX


2D object detection results.
This figure as: png eps pdf txt gnuplot



Bird's eye view results.
This figure as: png eps pdf txt gnuplot




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