第二届单目深度估计挑战赛
计算机视觉与模式识别
2023-04-27 v3 人工智能
摘要
本文讨论了第二届单目深度估计挑战赛（MDEC）的结果。本届赛事向使用任何形式监督的方法开放，包括全监督、自监督、多任务或代理深度。挑战赛基于 SYNS-Patches 数据集，该数据集具有高度多样化的环境及高质量稠密真值，包含复杂的自然环境（如森林或田野），而这些在当前基准中严重代表性不足。挑战赛收到了八份独特提交，其在任一基于点云或基于图像的指标上均优于所提供的 SotA 基线。排名最高的监督提交将相对 F-Score 提升了 27.62%，而排名最高的自监督提交提升了 16.61%。监督提交普遍利用大规模数据集集合以改善数据多样性；自监督提交则改进了网络架构与预训练骨干网络。这些结果代表了该领域的显著进展，同时指出了未来研究方向，如减少深度边界处的插值伪影、改善自监督室内性能以及整体自然图像精度。
引用
@article{arxiv.2304.07051,
title = {The Second Monocular Depth Estimation Challenge},
author = {Jaime Spencer and C. Stella Qian and Michaela Trescakova and Chris Russell and Simon Hadfield and Erich W. Graf and Wendy J. Adams and Andrew J. Schofield and James Elder and Richard Bowden and Ali Anwar and Hao Chen and Xiaozhi Chen and Kai Cheng and Yuchao Dai and Huynh Thai Hoa and Sadat Hossain and Jianmian Huang and Mohan Jing and Bo Li and Chao Li and Baojun Li and Zhiwen Liu and Stefano Mattoccia and Siegfried Mercelis and Myungwoo Nam and Matteo Poggi and Xiaohua Qi and Jiahui Ren and Yang Tang and Fabio Tosi and Linh Trinh and S. M. Nadim Uddin and Khan Muhammad Umair and Kaixuan Wang and Yufei Wang and Yixing Wang and Mochu Xiang and Guangkai Xu and Wei Yin and Jun Yu and Qi Zhang and Chaoqiang Zhao},
journal= {arXiv preprint arXiv:2304.07051},
year = {2023}
}
备注
Published at CVPRW2023