Lens-to-Lens Bokeh Effect Transformation. NTIRE 2023 Challenge Report
Lens-to-Lens Bokeh Effect Transformation. NTIRE 2023 Challenge Report
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DOI：
10.1109/cvprw59228.2023.00166
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
Marcos V. Conde;Manuel Kolmet;Tim Seizinger;†. TomE.Bishop;R. Timofte;Chengxin Liu;Xianrui Luo
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文献类型：
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作者：
Marcos V. Conde;Manuel Kolmet;Tim Seizinger;†. TomE.Bishop;R. Timofte;Chengxin Liu;Xianrui Luo
我们提出了新的Bokeh Effect Transformation Dataset（BETD），并在NTIRE 2023 Bokeh Effect Transformation Challenge上回顾了针对这一新任务提出的解决方案。移动的摄影的最新进展旨在达到全画幅相机的视觉质量。现在，计算摄影的一个目标是优化散景效果本身，这是图像失焦区域模糊的美学质量。摄影师通过利用透镜的光学特性来创造这种美学效果。这项工作的目的是设计一个神经网络，能够将一个透镜的散景效果转换为另一个透镜的效果，而不会损害图像中清晰的前景区域。对于给定的输入图像，在知道目标透镜类型的情况下，我们根据透镜属性渲染或变换散景效果。我们使用两台全画幅索尼相机和各种透镜设置构建了BETD。据我们所知，我们是解决这一新颖任务的第一次尝试，我们提供了第一个BETD数据集和基准测试。该挑战赛有99名注册参与者。提交的方法衡量了散景效果渲染和变换的最新水平。
We present the new Bokeh Effect Transformation Dataset (BETD), and review the proposed solutions for this novel task at the NTIRE 2023 Bokeh Effect Transformation Challenge. Recent advancements of mobile photography aim to reach the visual quality of full-frame cameras. Now, a goal in computational photography is to optimize the Bokeh effect itself, which is the aesthetic quality of the blur in out-of-focus areas of an image. Photographers create this aesthetic effect by benefiting from the lens optical properties.The aim of this work is to design a neural network capable of converting the the Bokeh effect of one lens to the effect of another lens without harming the sharp foreground regions in the image. For a given input image, knowing the target lens type, we render or transform the Bokeh effect accordingly to the lens properties. We build the BETD using two full-frame Sony cameras, and diverse lens setups.To the best of our knowledge, we are the first attempt to solve this novel task, and we provide the first BETD dataset and benchmark for it. The challenge had 99 registered participants. The submitted methods gauge the state-of-the-art in Bokeh effect rendering and transformation.