Reproduce “TriaGS: Differentiable Triangulation-Guided Geometric Consistency for 3D Gaussian Splatting” on OpenResearch
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About this paper
Quan Tran, Tuan Dang
TriaGS adds a self-supervised geometric consistency loss to 3D Gaussian Splatting, triangulating a rendered point projected into neighboring views and penalizing its difference from the original point. On 15 DTU scans, it reports mean Chamfer Distance of 0.50 mm, versus 0.53 mm for PGSR. This full-system comparison does not isolate the loss, and its projections are not independent observations.
Key insights
- Leveraging global multi-view triangulation provides a more robust and principled mechanism for geometric disambiguation and outlier rejection compared to local pairwise consistency checks.
- The use of a robust loss function (Geman-McClure) is critical for stable optimization with differentiable triangulation, as it prevents catastrophic divergence caused by sensitivity to outliers and large errors.
- Accurate, physically-grounded depth and normal maps are fundamental for effective multi-view geometric consistency enforcement, ensuring that triangulation operates on reliable 3D point data.
Summary by alphaXiv.
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