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Diminished reality (DR) refers to the removal of real objects from theenvironment by virtually replacing them with their background. Modern DRframeworks use inpainting to hallucinate unobserved regions. While recent deeplearning-based inpainting is promising, the DR use case is complicated by theneed to generate coherent structure and 3D geometry (i.e., depth), inparticular for advanced applications, such as 3D scene editing. In this paper,we propose DeepDR, a first RGB-D inpainting framework fulfilling allrequirements of DR: Plausible image and geometry inpainting with coherentstructure, running at real-time frame rates, with minimal temporal artifacts.Our structure-aware generative network allows us to explicitly condition colorand depth outputs on the scene semantics, overcoming the difficulty ofreconstructing sharp and consistent boundaries in regions with complexbackgrounds. Experimental results show that the proposed framework canoutperform related work qualitatively and quantitatively.

DeepDR: Deep Structure-Aware RGB-D Inpainting for Diminished Reality