Abstract
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.
Abstract (translated)
我们介绍了AquaFuse的概念，这是一种基于物理的方法，用于合成水下图像中的水域属性。我们制定了一个封闭形式的解决方案来融合水域，这有助于实现现实的数据增强和几何上一致的水下场景渲染。AquaFuse利用光在水中传播的物理特性，将一个场景中的水域合成为另一个场景中的物体内容。与数据驱动的风格迁移不同，AquaFuse能够保留输入场景中的深度一致性及对象几何结构。我们通过广泛的实验验证了这一独特特点，在不同的水下场景中进行测试。发现经过AquaFused处理的图像能保持超过94%的深度一致性和90-95%的输入场景结构相似度。我们还展示了它在保留物体几何形状的同时，适应固有的水域融合过程而生成准确的3D视图合成的能力。AquaFuse为数据增强开辟了一个新的研究方向，通过保形风格迁移来支持水下成像和机器人视觉应用。
URL
https://arxiv.org/abs/2411.01119
