第四届单目深度估计挑战
计算机视觉与模式识别
2025-04-25 v1
摘要
本文介绍了第四届单目深度估计挑战（MDEC）的结果，该挑战聚焦于对SYNS-Patches基准数据的零样本泛化，该数据集包含自然和室内环境中的具有挑战性场景。在本届中，我们修订了评估协议，采用最小二乘对齐（包含两个自由度）以支持视差和仿射不变的预测。我们也更新了基线方法，并包括了流行的即插即用方法：Depth Anything v2和Marigold。该挑战共收到24篇在测试集上超越基线的方法的提交，其中10篇包括描述其方法的报告，大多数领先方法依赖仿射不变的预测。挑战获胜者将3D F-Score提升至23.05%，显著超过上一届最佳结果的22.58%。
关键词
引用
@article{arxiv.2504.17787,
title = {The Fourth Monocular Depth Estimation Challenge},
author = {Anton Obukhov and Matteo Poggi and Fabio Tosi and Ripudaman Singh Arora and Jaime Spencer and Chris Russell and Simon Hadfield and Richard Bowden and Shuaihang Wang and Zhenxin Ma and Weijie Chen and Baobei Xu and Fengyu Sun and Di Xie and Jiang Zhu and Mykola Lavreniuk and Haining Guan and Qun Wu and Yupei Zeng and Chao Lu and Huanran Wang and Guangyuan Zhou and Haotian Zhang and Jianxiong Wang and Qiang Rao and Chunjie Wang and Xiao Liu and Zhiqiang Lou and Hualie Jiang and Yihao Chen and Rui Xu and Minglang Tan and Zihan Qin and Yifan Mao and Jiayang Liu and Jialei Xu and Yifan Yang and Wenbo Zhao and Junjun Jiang and Xianming Liu and Mingshuai Zhao and Anlong Ming and Wu Chen and Feng Xue and Mengying Yu and Shida Gao and Xiangfeng Wang and Gbenga Omotara and Ramy Farag and Jacket Demby and Seyed Mohamad Ali Tousi and Guilherme N DeSouza and Tuan-Anh Yang and Minh-Quang Nguyen and Thien-Phuc Tran and Albert Luginov and Muhammad Shahzad},
journal= {arXiv preprint arXiv:2504.17787},
year = {2025}
}
备注
To appear in CVPRW2025