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Computer Science > Computer Vision and Pattern Recognition

arXiv:2604.05581 (cs)
[Submitted on 7 Apr 2026]

Title:High-Resolution Single-Shot Polarimetric Imaging Made Easy

Authors:Shuangfan Zhou, Chu Zhou, Heng Guo, Youwei Lyu, Boxin Shi, Zhanyu Ma, Imari Sato
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Abstract: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.
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2604.05581 [cs.CV]
  (or arXiv:2604.05581v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2604.05581
arXiv-issued DOI via DataCite

Submission history

From: Shuangfan Zhou [view email]
[v1] Tue, 7 Apr 2026 08:20:58 UTC (26,219 KB)
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