# Multi-View Inpainting for RGB-D Sequence

arXiv: https://arxiv.org/abs/1811.09012 · HTML: https://mlsanity.com/paper/1811.09012/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Nov 2018.

## Built on by (most cited first, 4 of 4)

- [Overcoming Obstructions via Bandwidth-Limited Multi-Agent Spatial Handshaking](https://mlsanity.com/paper/2107.00771/) (2021)
- [Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting](https://mlsanity.com/paper/2304.03763/) (2023)
- [3DFill:Reference-guided Image Inpainting by Self-supervised 3D Image Alignment](https://mlsanity.com/paper/2211.04831/) (2022)
- [Defurnishing with X-Ray Vision: Joint Removal of Furniture from Panoramas and Mesh](https://mlsanity.com/paper/2506.05338/) (2025)

## Abstract (arXiv)

In this work we propose a novel approach to remove undesired objects from RGB-D sequences captured with freely moving cameras, which enables static 3D reconstruction. Our method jointly uses existing information from multiple frames as well as generates new one via inpainting techniques. We use balanced rules to select source frames; local homography based image warping method for alignment and Markov random field (MRF) based approach for combining existing information. For the left holes, we employ exemplar based multi-view inpainting method to deal with the color image and coherently use it as guidance to complete the depth correspondence. Experiments show that our approach is qualified for removing the undesired objects and inpainting the holes.