Structure-Aware Consistency Priors for Shape from Polarization in Complex Media

• URL: http://arxiv.org/abs/2606.00509v1
• Date: Sat, 30 May 2026 03:59:23 GMT
• Title: Structure-Aware Consistency Priors for Shape from Polarization in Complex Media
• Abstract summary: This paper focuses on ice as a representative complex medium, where intricate light matter interactions lead to a nonlinear mapping between polarization observations and surface normals.<n>A structure-aware polarization prior based on autocorrelation functions is proposed to capture the local spatial consistency of AoLP.<n>A dual-branch network (IceSfP) is designed to integrate raw polarization features with priors via cross modal attention and multi-scale feature fusion.
• Score: 0.7933039558471408
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recovering surface normals from single view polarization images in complex media remains challenging. This paper focuses on ice as a representative complex medium, where intricate light matter interactions lead to a nonlinear mapping between polarization observations and surface normals. To address this, a structure-aware polarization prior based on autocorrelation functions is proposed to capture the local spatial consistency of AoLP. Building on this, a dual-branch network (IceSfP) is designed to integrate raw polarization features with priors via cross modal attention and multi-scale feature fusion, enabling accurate surface normal estimation under complex media conditions. To evaluate the method, the first real-world ice SfP dataset is constructed. Experimental results show that the method outperforms existing approaches across all metrics, achieving a MAE of 16.01 deg, which is 2.74 deg lower than the second-best method. The framework provides a generalizable solution for high-precision geometric perception in complex media.

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