Method

MonoRoIDepth [MonoRoIDepth]
[Anonymous Submission]

Submitted on 1 May. 2023 15:25 by
[Anonymous Submission]

Running time:1 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
monoroidepth_rdiou_giou_matched_targets_depth_ave_2_
weighted_depth_supervised_l2_0.1_broadcast_loss_angl
e_focal_backbone_only_with_calibs_scale_0.4_shift_0.
25
Parameters:
152
threshold 0.2
with depth score
Latex Bibtex:

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) 93.99 % 88.45 % 78.50 %
Car (Orientation) 93.48 % 87.40 % 77.32 %
Car (3D Detection) 23.62 % 15.51 % 12.43 %
Car (Bird's Eye View) 32.11 % 21.85 % 18.20 %
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 txt gnuplot




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