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Dr. Bokeh: DiffeRentiable Occlusion-aware Bokeh Rendering

Yichen Sheng · Zixun Yu · Lu Ling · Zhiwen Cao · Xuaner Zhang · Xin Lu · Ke Xian · Haiting Lin · Bedrich Benes

Arch 4A-E Poster #424
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Wed 19 Jun 10:30 a.m. PDT — noon PDT


Bokeh is widely used in photography to draw attention to the subject while effectively isolating distractions in the background. Computational methods can simulate bokeh effects without relying on a physical camera lens, but the inaccurate lens modeling in existing filtering-based methods leads to artifacts that need post-processing or learning-based methods to fix. We propose Dr.Bokeh, a novel rendering method that addresses the issue by directly correcting the defect that violates the physics in the current filtering-based bokeh rendering equation. Dr.Bokeh first preprocesses the input RGBD to obtain a layered scene representation. Dr.Bokeh then takes the layered representation and user-defined lens parameters to render photo-realistic lens blur based on the novel occlusion-aware bokeh rendering method. Experiments show that the non-learning based renderer Dr.Bokeh outperforms state-of-the-art bokeh rendering algorithms in terms of photo-realism.In addition, extensive quantitative and qualitative evaluations show the more accurate lens model further pushes the limit of a closely related field depth-from-defocus.

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