第三届单目深度估计挑战赛
计算机视觉与模式识别
2024-04-30 v2
摘要
本文讨论了第三届单目深度估计挑战赛(MDEC)的结果。该挑战赛聚焦于对具有挑战性的 SYNS-Patches 数据集的零样本泛化能力,该数据集包含自然和室内环境下的复杂场景。与上一届一样,参赛方法可使用任何形式的监督,即有监督或自监督。本次挑战赛共收到 19 份在测试集上超越基线的提交,其中 10 份提交了描述其方法的报告,凸显了基础模型(如 Depth Anything)在其方法核心的广泛使用。挑战赛获胜者将 3D F-Score 性能从 17.51% 大幅提升至 23.72%。
引用
@article{arxiv.2404.16831,
title = {The Third Monocular Depth Estimation Challenge},
author = {Jaime Spencer and Fabio Tosi and Matteo Poggi and Ripudaman Singh Arora and Chris Russell and Simon Hadfield and Richard Bowden and GuangYuan Zhou and ZhengXin Li and Qiang Rao and YiPing Bao and Xiao Liu and Dohyeong Kim and Jinseong Kim and Myunghyun Kim and Mykola Lavreniuk and Rui Li and Qing Mao and Jiang Wu and Yu Zhu and Jinqiu Sun and Yanning Zhang and Suraj Patni and Aradhye Agarwal and Chetan Arora and Pihai Sun and Kui Jiang and Gang Wu and Jian Liu and Xianming Liu and Junjun Jiang and Xidan Zhang and Jianing Wei and Fangjun Wang and Zhiming Tan and Jiabao Wang and Albert Luginov and Muhammad Shahzad and Seyed Hosseini and Aleksander Trajcevski and James H. Elder},
journal= {arXiv preprint arXiv:2404.16831},
year = {2024}
}
备注
To appear in CVPRW2024