The KITTI Vision Benchmark Suite

Method

DA3D+KM3D+v2-99 [DA3D+KM3D+v2-99]

Submitted on 17 Feb. 2024 12:48 by
贾译凇 (哈尔滨工业大学)

Running time:		0.120s
Environment:		GPU @ 2.5 Ghz (Python)

Method Description:

DA3D+KM3D+v2-99

Parameters:

DA3D+KM3D+v2-99

Latex Bibtex:

@ARTICLE{10497146,
author={Jia, Yisong and Wang, Jue and Pan, Huihui and Sun, Weichao},
journal={IEEE Transactions on Instrumentation and Measurement},
title={Enhancing Monocular 3-D Object Detection Through Data Augmentation Strategies},
year={2024},
volume={73},
number={},
pages={1-11},
keywords={Three-dimensional displays;Object detection;Data augmentation;Task analysis;Pipelines;Cameras;Detectors;Autonomous driving;data augmentation;deep learning;monocular 3-D object detection},
doi={10.1109/TIM.2024.3387500}}

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 (Orientation)	0.00 %	0.00 %	0.00 %
Car (3D Detection)	34.72 %	26.80 %	23.05 %
Car (Bird's Eye View)	44.27 %	34.88 %	30.29 %
Pedestrian (Detection)	0.00 %	0.00 %	0.00 %
Pedestrian (Orientation)	0.00 %	0.00 %	0.00 %
Pedestrian (3D Detection)	9.38 %	6.32 %	5.54 %
Pedestrian (Bird's Eye View)	10.32 %	7.06 %	6.10 %
Cyclist (Detection)	0.00 %	0.00 %	0.00 %
Cyclist (Orientation)	0.00 %	0.00 %	0.00 %
Cyclist (3D Detection)	8.58 %	5.11 %	4.48 %
Cyclist (Bird's Eye View)	9.73 %	5.82 %	4.88 %