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From Explicit References to Scene Manifolds: Distributional Fidelity and Realism for Radiance Field Quality Assessment

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Radiance field representations such as 3D Gaussian Splatting (3DGS) enable high-quality novel view synthesis but can introduce complex, view-dependent artifacts from reconstruction, rendering, and compression. Reliable perceptual quality assessment (QA) is thus essential for evaluating rendered views and guiding the design of perceptually faithful scene representations. Existing full-reference QA metrics require an aligned reference image, while recent cross-reference metrics relax this requirement by comparing a test view with non-aligned references. However, under wide-baseline radiance fiel

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