Oblique-MERF: Revisiting and improving MERF for oblique photography

Zeng, Xiaoyi, Song, Kaiwen, Yang, Leyuan, Deng, Bailin ORCID: https://orcid.org/0000-0002-0158-7670 and Zhang, Juyong 2025. Oblique-MERF: Revisiting and improving MERF for oblique photography. Presented at: International Conference on 3D Vision, Singapore, 25-28 March 2025.

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Abstract

Neural radiance fields (NeRF) have established a new paradigm for 3D scene reconstruction, with subsequent work achieving high-quality real-time rendering. However, reconstructing large-scale scenes from oblique aerial photography presents unique challenges, such as varying spatial scale distributions and a constrained range of tilt angles, often resulting in high memory consumption and reduced rendering quality at extrapolated viewpoints. To address these issues, we propose a novel approach named Oblique-MERF to accommodate the distinctive characteristics of oblique photography datasets and support real-time rendering on various common devices. Firstly, an innovative adaptive occupancy plane is proposed to constrain the sampling space. Additionally, we propose a smoothness regularization loss for view-dependent color to enhance the MLP's ability to generalize to untrained viewpoints. Experimental results demonstrate that Oblique-MERF reduces VRAM usage by approximately $40\%$ while maintaining competitive rendering quality compared to baseline methods, and achieves higher frame rates with more realistic rendering even at untrained extrapolated viewpoints. Project page: https://ustc3dv.github.io/Oblique-MERF/

Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Date of First Compliant Deposit:	4 January 2025
Date of Acceptance:	6 November 2024
Last Modified:	17 Jan 2025 11:15
URI:	https://orca.cardiff.ac.uk/id/eprint/174989

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