αSurf: implicit surface reconstruction for semi-transparent and thin objects with decoupled geometry and opacity
File(s)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Implicit surface representations such as the signed distance function (SDF) have emerged as a promising approach for image-based surface reconstruction. However, existing optimization methods assume opaque surfaces and therefore cannot properly reconstruct translucent surfaces and sub-pixel thin structures, which also exhibit low opacity due to the blending effect. While neural radiance field (NeRF) based methods can model semi-transparency and synthesize novel views with photo-realistic quality, their volumetric representation tightly couples geometry (surface occupancy) and material property (surface opacity), and therefore cannot be easily converted into surfaces without introducing artifacts. We present α Surf, a novel scene representation with decoupled geometry and opacity for the reconstruction of surfaces with translucent or blending effects. Ray-surface intersections on our representation can be found in closed-form via analytical solutions of cubic polynomials, avoiding Monte-Carlo sampling, and are fully differentiable by construction. Our qualitative and quantitative evaluations show that our approach can accurately reconstruct translucent and extremely thin surfaces, achieving better reconstruction quality than state-of-the-art SDF and NeRF methods.
Date Issued
2025-03-25
Date Acceptance
2025-03-25
Citation
International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2025, pp.44-63
ISBN
979-8-3315-3851-4
ISSN
2475-7888
Publisher
IEEE
Start Page
44
End Page
63
Journal / Book Title
International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)
Copyright Statement
Copyright © 2025 IEEE. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Source
2025 International Conference on 3D Vision (3DV)
Publication Status
Published
Start Date
2025-03-25
Finish Date
2025-03-28
Coverage Spatial
Singapore, Singapore
Date Publish Online
2025-08-25