EB-RANSAC: Random Sample Consensus based on Energy-Based Model

Muneki Yasuda; Nao Watanabe; Kaiji Sekimoto

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arXiv · 2603.12525

EB-RANSAC: Random Sample Consensus based on Energy-Based Model

Muneki Yasuda·Nao Watanabe·Kaiji Sekimoto

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Abstract

Random sample consensus (RANSAC), which is based on a repetitive sampling from a given dataset, is one of the most popular robust estimation methods. In this study, an energy-based model (EBM) for robust estimation that has a similar scheme to RANSAC, energy-based RANSAC (EB-RANSAC), is proposed. EB-RANSAC is applicable to a wide range of estimation problems similar to RANSAC. However, unlike RANSAC, EB-RANSAC does not require a troublesome sampling procedure and has only one hyperparameter. The effectiveness of EB-RANSAC is numerically demonstrated in two applications: a linear regression and maximum likelihood estimation.

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BibTeX RIS

Muneki Yasuda, Nao Watanabe, Kaiji Sekimoto. 2026-03-12. EB-RANSAC: Random Sample Consensus based on Energy-Based Model. https://arxiv.org/abs/2603.12525

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