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The Fourth Monocular Depth Estimation Challenge
Conference proceeding   Open access

The Fourth Monocular Depth Estimation Challenge

Anton Obukhov, Matteo Poggi, Fabio Tosi, Ripudaman Singh Arora, Jaime Spencer, Chris Russell, Simon Hadfield, Richard Bowden, Shuaihang Wang, Zhenxin Ma, …
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2025), pp.6172-6185
The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2025 (Nashville, TN, USA, 11/06/2025–16/06/2025)
11/06/2025
DOI: https://doi.org/10.1109/CVPRW67362.2025.00615

Abstract

2-DOF Benchmark testing Conferences Depth measurement monocular depth estimation Protocols Three-dimensional displays Computer Vision Pattern Recognition
This paper presents the results of the fourth edition of the Monocular Depth Estimation Challenge (MDEC), which focuses on zero-shot generalization to the SYNS-Patches benchmark, a dataset featuring challenging environments in both natural and indoor settings. In this edition, we revised the evaluation protocol to use least-squares alignment with two degrees of freedom to support disparity and affineinvariant predictions. We also revised the baselines and included popular off-the-shelf methods: Depth Anything v2 and Marigold. The challenge received a total of 24 submissions that outperformed the baselines on the test set; 10 of these included a report describing their approach, with most leading methods relying on affine-invariant predictions. The challenge winners improved the 3D F-Score over the previous edition's best result, raising it from 22.58 % to 23.05 %.
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https://doi.org/10.1109/CVPRW67362.2025.00615View
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