Multi-View Inpainting for RGB-D Sequence
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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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Nov 2018.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 1.
4 papers.
- 2021Overcoming Obstructions via Bandwidth-Limited Multi-Agent Spatial Handshakingcited by 16
- 2023Clutter Detection and Removal in 3D Scenes with View-Consistent Inpaintingcited by 9
- 20223DFill:Reference-guided Image Inpainting by Self-supervised 3D Image Alignmentcited by 3
- 2025Defurnishing with X-Ray Vision: Joint Removal of Furniture from Panoramas and Meshcited by 0
- 2025Defurnishing with X-Ray Vision: Joint Removal of Furniture from Panoramas and Mesh5 Jun 2025
- 2023Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting7 Apr 2023
- 20223DFill:Reference-guided Image Inpainting by Self-supervised 3D Image Alignment9 Nov 2022
- 2021Overcoming Obstructions via Bandwidth-Limited Multi-Agent Spatial Handshaking1 Jul 2021