We present a method for estimating lighting from a single perspective image of an indoor scene. Previous methods for predicting indoor illumination usually focus on either simple, parametric lighting that lack realism, or on richer representations that are difficult or even impossible to understand or modify after prediction. We propose a pipeline that estimates a parametric light that is easy to edit and allows renderings with strong shadows, alongside with a non-parametric texture with high-frequency information necessary for realistic rendering of specular objects. Once estimated, the predictions obtained with our model are interpretable and can easily be modified by an artist/user with a few mouse clicks. Quantitative and qualitative results show that our approach makes indoor lighting estimation easier to handle by a casual user, while still producing competitive results.

翻译：我们提出了一个从室内景象的单一角度来估计照明的方法。先前的室内照明预测方法通常侧重于简单、缺乏现实性的参数照明,或者侧重于在预测后难以理解甚至无法理解或修改的更丰富的表情。我们建议建立一个管道,对易于编辑的参数光线进行估算,并允许使用强烈阴影的图象,同时使用非参数纹理和高频信息,以便现实地投放显眼物体。经过估算,我们模型获得的预测是可以解释的,并且可以很容易地由艺术家/用户用鼠标点击修改。定量和定性结果表明,我们的方法使得室内照明估计更容易由临时用户处理,同时仍然产生竞争性的结果。