用物理模型融合水体效果，让水下图像合成更真实且保持几何一致。
AquaFuse: Waterbody Fusion for Physics Guided View Synthesis of Underwater Scenes
- 基于光在水下传播的物理规律，实现水体与物体的精准融合。
- 合成图像深度一致性超94%，结构相似度达90%-95%。
- 适合需要几何保真的水下视觉、机器人导航等场景。
我们提出AquaFuse，一种基于物理规律的水下图像水体属性合成方法。通过构建水体融合的闭式解，实现真实的数据增强和几何一致的水下场景渲染。AquaFuse利用水下光传播特性，将一个场景的水体特征融合到另一个场景的物体内容中。与数据驱动的风格迁移不同，AquaFuse保持输入场景的深度一致性和物体几何结构。在多样水下场景上的全面实验表明，AquaFused图像保留了超过94%的深度一致性，以及90%-95%的结构相似性。同时，该方法在保持物体几何的前提下，实现了准确的3D视角合成。AquaFuse为水下成像与机器人视觉中的几何保真风格迁移开辟了新方向。
原文摘要 · Abstract (English)
We introduce the idea of AquaFuse, a physics-based method for synthesizing waterbody properties in underwater imagery. We formulate a closed-form solution for waterbody fusion that facilitates realistic data augmentation and geometrically consistent underwater scene rendering. AquaFuse leverages the physical characteristics of light propagation underwater to synthesize the waterbody from one scene to the object contents of another. Unlike data-driven style transfer, AquaFuse preserves the depth consistency and object geometry in an input scene. We validate this unique feature by comprehensive experiments over diverse underwater scenes. We find that the AquaFused images preserve over 94% depth consistency and 90-95% structural similarity of the input scenes. We also demonstrate that it generates accurate 3D view synthesis by preserving object geometry while adapting to the inherent waterbody fusion process. AquaFuse opens up a new research direction in data augmentation by geometry-preserving style transfer for underwater imaging and robot vision applications.
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