Method

CDN-PL++[st] [CDN-PL++]


Submitted on 5 Jun. 2020 18:45 by
Yan Wang (Cornell University)

Running time:0.4 s
Environment:GPU @ 2.5 Ghz (C/C++)

Method Description:
CDN-PL++
Parameters:
CDN-PL++
Latex Bibtex:
@article{garg2020wasserstein,
title={Wasserstein Distances for Stereo Disparity
Estimation},
author={Garg, Divyansh and Wang, Yan and
Hariharan, Bharath and Campbell, Mark and
Weinberger, Kilian Q and Chao, Wei-Lun},
journal={Advances in Neural Information
Processing Systems},
volume={33},
year={2020}
}

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) 94.66 % 85.01 % 77.60 %
Car (Orientation) 94.45 % 84.21 % 76.69 %
Car (3D Detection) 64.31 % 44.86 % 38.11 %
Car (Bird's Eye View) 81.27 % 61.04 % 52.84 %
This table as LaTeX

2D object detection results.
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Orientation estimation results.
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3D object detection results.
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Bird's eye view results.
This figure as: png eps pdf txt gnuplot




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