# High-Resolution Single-Shot Polarimetric Imaging Made Easy

arXiv: https://arxiv.org/abs/2604.05581 · HTML: https://mlsanity.com/paper/2604.05581/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 43 references that are in the map.
- First posted on arXiv 7 Apr 2026.

## Builds on (most cited first, 1 of 1)

- [RGB-to-Polarization Estimation: A New Task and Benchmark Study](https://mlsanity.com/paper/2505.13050/) (2025)

## Abstract (arXiv)

Polarization-based vision has gained increasing attention for providing richer physical cues beyond RGB images. While achieving single-shot capture is highly desirable for practical applications, existing Division-of-Focal-Plane (DoFP) sensors inherently suffer from reduced spatial resolution and artifacts due to their spatial multiplexing mechanism. To overcome these limitations without sacrificing the snapshot capability, we propose EasyPolar, a multi-view polarimetric imaging framework. Our system is grounded in the physical insight that three independent intensity measurements are sufficient to fully characterize linear polarization. Guided by this, we design a triple-camera setup consisting of three synchronized RGB cameras that capture one unpolarized view and two polarized views with distinct orientations. Building upon this hardware design, we further propose a confidence-guided polarization reconstruction network to address the potential misalignment in multi-view fusion. The network performs multi-modal feature fusion under a confidence-aware physical guidance mechanism, which effectively suppresses warping-induced artifacts and enforces explicit geometric constraints on the solution space. Experimental results demonstrate that our method achieves high-quality results and benefits various downstream tasks.