Partial occlusion effects are a phenomenon that blurry objects near a camera are semi-transparent, resulting in partial appearance of occluded background. However, it is challenging for existing bokeh rendering methods to simulate realistic partial occlusion effects due to the missing information of the occluded area in an all-in-focus image. Inspired by the learnable 3D scene representation, Multiplane Image (MPI), we attempt to address the partial occlusion by introducing a novel MPI-based high-resolution bokeh rendering framework, termed MPIB. To this end, we first present an analysis on how to apply the MPI representation to bokeh rendering. Based on this analysis, we propose an MPI representation module combined with a background inpainting module to implement high-resolution scene representation. This representation can then be reused to render various bokeh effects according to the controlling parameters. To train and test our model, we also design a ray-tracing-based bokeh generator for data generation. Extensive experiments on synthesized and real-world images validate the effectiveness and flexibility of this framework.
翻译:部分封闭效应是一种现象,即照相机附近的模糊物体半透明,导致部分隐蔽背景出现。然而,由于全聚焦图像中隐蔽区域缺少信息,现有bokeh 模拟现实部分封闭效应的方法具有挑战性,因为全聚焦图像中隐蔽区域缺少信息。受可学的 3D 场景演示,多平面图像(MPI)的启发,我们试图通过引入一个以 MPI 为基础的新型高分辨率bokeh 放大框架(称为 MPIB) 来解决部分封闭问题。为此,我们首先对如何应用MPI 表示法进行一项分析。根据这一分析,我们提议一个MPI 代表模块,加上一个背景涂色模块,以实施高分辨率场演示。然后,这种表达法可以再利用,根据控制参数产生各种隐蔽效应。为了培训和测试我们的模型,我们还设计了一个基于光色的bokeh生成数据的生成器。关于合成和真实世界图像的广泛实验,以证实这一框架的有效性和灵活性。