Layout Aware Inpainting for Automated Furniture Removal in Indoor Scenes
Prakhar Kulshreshtha, Konstantinos-Nektarios Lianos, Brian Pugh and, Salma Jiddi

TL;DR
This paper presents a layout-aware inpainting method for automatically removing furniture from indoor scene images, ensuring geometric consistency and enabling virtual redecoration.
Contribution
It introduces a novel approach utilizing perceptual information like instance segmentation and room layout for geometrically consistent inpainting of large regions.
Findings
Effective furniture removal with geometric consistency
Automatic rectification improves inpainting quality
Application demonstrated with virtual redecoration
Abstract
We address the problem of detecting and erasing furniture from a wide angle photograph of a room. Inpainting large regions of an indoor scene often results in geometric inconsistencies of background elements within the inpaint mask. To address this problem, we utilize perceptual information (e.g. instance segmentation, and room layout) to produce a geometrically consistent empty version of a room. We share important details to make this system viable, such as per-plane inpainting, automatic rectification, and texture refinement. We provide detailed ablation along with qualitative examples, justifying our design choices. We show an application of our system by removing real furniture from a room and redecorating it with virtual furniture.
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Taxonomy
TopicsGenerative Adversarial Networks and Image Synthesis · Advanced Vision and Imaging · 3D Surveying and Cultural Heritage
MethodsInpainting
