MACE: Mixture-of-Experts Accelerated Coordinate Encoding for Large-Scale Scene Localization and Rendering

Mingkai Liu; Dikai Fan; Haohua Que; Haojia Gao; Xiao Liu; Shuxue Peng; Meixia Lin; Shengyu Gu; Ruicong Ye; Wanli Qiu; Handong Yao; Ruopeng Zhang; Xianliang Huang

arXiv · 2510.14251

MACE: Mixture-of-Experts Accelerated Coordinate Encoding for Large-Scale Scene Localization and Rendering

Mingkai Liu·Dikai Fan·Haohua Que·Haojia Gao·Xiao Liu·Shuxue Peng·Meixia Lin·Shengyu Gu·Ruicong Ye·Wanli Qiu·Handong Yao·Ruopeng Zhang·Xianliang Huang

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Abstract

Efficient localization and high-quality rendering in large-scale scenes remain a significant challenge due to the computational cost involved. While Scene Coordinate Regression (SCR) methods perform well in small-scale localization, they are limited by the capacity of a single network when extended to large-scale scenes. To address these challenges, we propose the Mixed Expert-based Accelerated Coordinate Encoding method (MACE), which enables efficient localization and high-quality rendering in large-scale scenes. Inspired by the remarkable capabilities of MOE in large model domains, we introduce a gating network to implicitly classify and select sub-networks, ensuring that only a single sub-network is activated during each inference. Furtheremore, we present Auxiliary-Loss-Free Load Balancing(ALF-LB) strategy to enhance the localization accuracy on large-scale scene. Our framework provides a significant reduction in costs while maintaining higher precision, offering an efficient solution for large-scale scene applications. Additional experiments on the Cambridge test set demonstrate that our method achieves high-quality rendering results with merely 10 minutes of training.

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Mingkai Liu, Dikai Fan, Haohua Que, Haojia Gao, Xiao Liu, Shuxue Peng, Meixia Lin, Shengyu Gu, Ruicong Ye, Wanli Qiu, Handong Yao, Ruopeng Zhang, Xianliang Huang. 2025-10-16. MACE: Mixture-of-Experts Accelerated Coordinate Encoding for Large-Scale Scene Localization and Rendering. https://arxiv.org/abs/2510.14251

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