arXiv:2610.34597 · v1

Finetuning Prompt-Based Image Editor for Geometry-Consistent Room Defurnishing

首次提交 2026-10-26 05:54

版本更新 2026-10-26 05:54

雷达观测 2026-10-29 00:36

摘要

Erasing all furniture from a single room image to generate its empty counterpart is valuable for XR applications such as diminished reality and virtual staging. The challenge is twofold: inpainting the furniture regions with realistic content, and doing so without distorting the room's 3D geometry. Prompt-driven image editors, such as FLUX.2, handle realism impressively, but their structural faithfulness is inferior to explicit layout conditioned inpainting. To improve geometric consistency, we propose a training recipe for finetuning a LoRA on 2,500 furnished-empty room pairs. FLUX.2 with our LoRA adaptor significantly improves geometric consistency while retaining the high texture fidelity. This single-photo inpainter can be an effective building block for depth-aware and 3D-consistent XR pipelines.

作者备注：2 pages, 3 figures. Poster presented at IEEE ISMAR 2026 (non-archival)