偏振状态追踪用于去反射与色彩一致重建
Polarization State Tracing for Reflection Removal and Color-Consistent Reconstruction
将偏振光在玻璃内的多路径传播与波长选择性吸收显式建模为成像模型（PSTM），为透过有色介质的去反射与色彩一致性复原提供了可复用的物理先验；其通道环形注意力（CRA）用于建模偏振通道间的角度依赖，可迁移到其他多通道/多视角偏振特征融合任务，恢复的偏振信息还能直接服务 Shape-from-Polarization 等下游几何任务。
原文依据 we propose a novel imaging model, the Polarization State Tracing Model (PSTM), which traces polarized light along multiple propagation paths
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论有色玻璃在日常生活中被广泛使用，但其反射与吸收特性往往会在拍摄图像中引入鬼影与色偏。然而，现有方法通常忽略吸收问题，因而难以处理有色玻璃造成的色偏。为此，我们首次将偏振成像理论应用于玻璃内部光传输过程的建模。具体而言，我们提出一种新的成像模型——偏振状态追踪模型（PSTM），它沿多条传播路径追踪偏振光并考虑波长选择性吸收，从而实现去反射与色彩一致重建的联合求解。在 PSTM 的引导下，我们设计了通道环形注意力（CRA）机制，以高效捕捉角度间的偏振依赖关系并增强偏振通道间的特征交互，从而保证恢复结果的物理一致性。此外，恢复出的偏振信息可直接应用于 Shape-from-Polarization（SfP）等高级下游任务。我们构建了真实世界数据集 GlassPol，涵盖多种玻璃材质，可在多样光学条件下进行测试。大量实验表明，我们的方法优于现有最优方法，PSNR 最高提升 3dB，为偏振去反射建立了新的基准。
英文原文摘要 1402 字符
Colored glass is widely used in everyday settings, yet its reflective and absorptive properties often introduce ghost shadows and color bias in captured images. However, existing methods typically neglect the absorption issue, making it difficult to address color bias caused by colored glass. To address this, we are the first to apply polarization imaging theory to model the light transmission process within glass. Specifically, we propose a novel imaging model, the Polarization State Tracing Model (PSTM), which traces polarized light along multiple propagation paths and accounts for wavelength-selective absorption, enabling joint reflection removal and color-consistent reconstruction. Guided by PSTM, we design a Channel Ring Attention (CRA) mechanism to efficiently capture inter-angle polarization dependencies and enhance feature interaction across polarization channels, ensuring physically consistent recovery. Besides, the recovered polarization information can be directly applied to advanced downstream tasks, such as Shape-from-Polarization (SfP). We construct a real-world dataset, GlassPol, containing a wide range of glass materials, enabling testing under diverse optical conditions. Extensive experiments show that our method outperforms existing state-of-the-art methods, achieving up to a 3dB improvement in PSNR, establishing a new benchmark for polarized reflection removal.