Author

Marco Di Benedetto

2 papers indexed here

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#artificial intelligence Jun 2026

Resonant Brane Splatting for Arbitrary-Scale Super-Resolution

Resonant Brane Splatting (RBS) is introduced, a feed-forward ASR framework that introduces an efficient fully differentiable rasterizer with a precise culling strategy based on the classical quantum turning point that allows it to safely skip negligible regions, drastically reducing the rendering overhead.

Giulio Federico, Giuseppe Amato, C. Gennaro et al. · arXiv.org · 0 citations

#artificial intelligence Preprint Jun 2026

Adaptive Densification for High-Fidelity and Efficient Sparse Gaussian Splatting in Arbitrary-Scale Super-Resolution

QuADA-GS is proposed, an approach that retains a powerful representational backbone but autonomously predicts where to allocate Gaussians relying strictly on the low-resolution input, providing an improved and competitive trade-off for ASR.

Giulio Federico, Giuseppe Amato, C. Gennaro et al. · 0 citations