The Monocular Depth Estimation Challenge
The Monocular Depth Estimation Challenge
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DOI：
10.1109/wacvw58289.2023.00069
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
Jaime Spencer;C. Qian;Chris Russell;Simon Hadfield;E. Graf;W. Adams;A. Schofield;J. Elder;R. Bowden;Heng Cong;S. Mattoccia;Matteo Poggi;Zeeshan Khan Suri;Yang Tang;Fabio Tosi;Hao Wang;Youming Zhang;Yusheng Zhang;Chaoqiang Zhao
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文献类型：
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作者：
Jaime Spencer;C. Qian;Chris Russell;Simon Hadfield;E. Graf;W. Adams;A. Schofield;J. Elder;R. Bowden;Heng Cong;S. Mattoccia;Matteo Poggi;Zeeshan Khan Suri;Yang Tang;Fabio Tosi;Hao Wang;Youming Zhang;Yusheng Zhang;Chaoqiang Zhao
本文总结了在WACV 2023上组织的第一次单目深度估计挑战赛（MDEC）的结果。这项挑战评估了在具有挑战性的SYNS-Patches数据集上进行自监督单目深度估计的进展。该挑战赛是在CodaLab上组织的，并收到了来自4个有效团队的提交。参与者获得了一个devkit，其中包含16种最新算法和4种新技术的更新参考实现。接受新技术的阈值是优于16个SotA基线中的每一个。所有参与者在传统指标（如MAE或AbsRel）中的表现都优于基线。然而，点云重建指标具有挑战性的改进。我们发现预测的特点是插值文物在对象边界和相对对象定位的错误。我们希望这个挑战是对社区的宝贵贡献，并鼓励作者参与未来的版本。
This paper summarizes the results of the first Monocular Depth Estimation Challenge (MDEC) organized at WACV2023. This challenge evaluated the progress of self-supervised monocular depth estimation on the challenging SYNS-Patches dataset. The challenge was organized on CodaLab and received submissions from 4 valid teams. Participants were provided a devkit containing updated reference implementations for 16 State-of-the-Art algorithms and 4 novel techniques. The threshold for acceptance for novel techniques was to outperform every one of the 16 SotA baselines. All participants outperformed the baseline in traditional metrics such as MAE or AbsRel. However, pointcloud reconstruction metrics were challenging to improve upon. We found predictions were characterized by interpolation artefacts at object boundaries and errors in relative object positioning. We hope this challenge is a valuable contribution to the community and encourage authors to participate in future editions.