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NeRF synthesis with shading guidance

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arxiv 2306.11556 v1 pith:IX2EDHWM submitted 2023-06-20 cs.CV cs.GR

classification cs.CVcs.GR
keywords scenesnerflightingmethodsynthesisappearancearbitraryeffects
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The emerging Neural Radiance Field (NeRF) shows great potential in representing 3D scenes, which can render photo-realistic images from novel view with only sparse views given. However, utilizing NeRF to reconstruct real-world scenes requires images from different viewpoints, which limits its practical application. This problem can be even more pronounced for large scenes. In this paper, we introduce a new task called NeRF synthesis that utilizes the structural content of a NeRF patch exemplar to construct a new radiance field of large size. We propose a two-phase method for synthesizing new scenes that are continuous in geometry and appearance. We also propose a boundary constraint method to synthesize scenes of arbitrary size without artifacts. Specifically, we control the lighting effects of synthesized scenes using shading guidance instead of decoupling the scene. We have demonstrated that our method can generate high-quality results with consistent geometry and appearance, even for scenes with complex lighting. We can also synthesize new scenes on curved surface with arbitrary lighting effects, which enhances the practicality of our proposed NeRF synthesis approach.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. NeRF-Texture: Synthesizing Neural Radiance Field Textures

    cs.CV 2024-12 conditional novelty 7.0 of 10

    A NeRF-based representation plus latent patch-matching algorithm that synthesizes meso-structure textures from multi-view images and maps them onto new 3D shapes.

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