#7355. RGB-Fusion: Monocular 3D reconstruction with learned depth prediction
October 2026 | publication date |
Proposal available till | 28-05-2025 |
4 total number of authors per manuscript | 0 $ |
The title of the journal is available only for the authors who have already paid for |
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Journal’s subject area: |
Electrical and Electronic Engineering;
Hardware and Architecture;
Human-Computer Interaction; |
Places in the authors’ list:
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)
Abstract:
Generating large-scale and high-quality 3D scene reconstruction from monocular images is an essential technical foundation in augmented reality and robotics. However, the apparent shortcomings make applying monocular 3D reconstruction to real-world practice challenging. In this work, we combine the advantage of deep learning and multi-view geometry to propose RGB-Fusion, which effectively solves the inherent limitations of traditional monocular reconstruction.
Keywords:
Depth refinement; Monocular 3D reconstruction; PnP algorithm; Pose estimation
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