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20242026
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cs.CV2026

Compact Neural Appearance Models for Efficient Gaussian Splatting

Florian Hahlbohm, Jorge Condor, Linus Franke +2

Explicit primitive-based radiance fields such as 3D Gaussian Splatting typically model view-dependent appearance using low-order spherical harmonics (SH). Although efficient to eva…

cs.CV2026

Beyond Spherical Harmonics: Rethinking Appearance Models for Radiance Reconstruction

Ewa Miazga, Jorge Condor, Piotr Didyk

View-dependent appearance modeling remains a challenging problem in novel-view synthesis and reconstruction. Accurately representing complex angular effects often requires substant…

cs.CV2026

Neural Harmonic Textures for High-Quality Primitive Based Neural Reconstruction

Jorge Condor, Nicolas Moenne-Loccoz, Merlin Nimier-David +3

Primitive-based methods such as 3D Gaussian Splatting have recently become the state-of-the-art for novel-view synthesis and related reconstruction tasks. Compared to neural fields…

cs.CV2024

Human Vision Constrained Super-Resolution

Volodymyr Karpenko, Taimoor Tariq, Jorge Condor +1

Modern deep-learning super-resolution (SR) techniques process images and videos independently of the underlying content and viewing conditions. However, the sensitivity of the huma…

cs.CV2024

Puzzle Similarity: A Perceptually-guided Cross-Reference Metric for Artifact Detection in 3D Scene Reconstructions

Nicolai Hermann, Jorge Condor, Piotr Didyk

Modern reconstruction techniques can effectively model complex 3D scenes from sparse 2D views. However, automatically assessing the quality of novel views and identifying artifacts…