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F-RNG framework generates relightable 3D assets from sparse views

By PulseAugur Editorial · [2 sources] ·

Researchers have developed F-RNG, a novel feed-forward framework designed to generate relightable 3D Gaussian Splatting (3DGS) assets from sparse-view inputs. This approach leverages existing large reconstruction models (LRMs) and intrinsic decomposition models (IDMs) to extract relightable representations without requiring extensive retraining. F-RNG enhances geometry synthesis and uses prior-guided distillation for appearance, enabling flexible relighting with significantly reduced computational cost and faster inference times compared to state-of-the-art methods. AI

IMPACT Enables faster and more cost-effective creation of relightable 3D assets, potentially impacting real-time rendering and virtual environments.

RANK_REASON The cluster contains a research paper detailing a new method for 3D asset generation.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

F-RNG framework generates relightable 3D assets from sparse views

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The cluster contains a research paper detailing a new method for 3D asset generation.
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124 days old
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Guangming Fu, Jiahui Fan, Jian Yang, Milo\v{s} Ha\v{s}an, Beibei Wang ·

    F-RNG: Feed-Forward Relightable Neural Gaussians

    arXiv:2605.25975v1 Announce Type: cross Abstract: Capturing relightable 3D assets from real-world objects is a widely researched problem. Several per-scene optimization-based methods, based on 3D Gaussian splatting (3DGS), support relighting; however, they usually require dense i…

  2. arXiv cs.CV TIER_1 English(EN) · Beibei Wang ·

    F-RNG: Feed-Forward Relightable Neural Gaussians

    Capturing relightable 3D assets from real-world objects is a widely researched problem. Several per-scene optimization-based methods, based on 3D Gaussian splatting (3DGS), support relighting; however, they usually require dense input views, and their overfitting nature makes it …

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