Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation
Hadi Alzayer, Philipp Henzler, Jonathan T. Barron, Jia-Bin Huang, Pratul P. Srinivasan, Dor Verbin
Abstract
https://relight-to-reconstruct.github.io/ Input images with varying illumination Novel views under reference illumination Ours Baseline Reference light Ground truth Figure 1. 3D reconstruction under extreme illumination variation. We propose a method for 3D reconstruction from a set of images captured under strongly varying illumination. Our method recovers high-fidelity appearance details including specular highlights that prior state-of-the-art approaches cannot recover (top baseline: NeRF-Casting [47] with appearance embeddings, bottom baseline: NeROIC [25]).
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Install the CLIlune papers fulltext d886e9c9-3deb-402a-937e-077257c05ca1Cited by top-tier papers10
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- CAT3D: Create Anything in 3D with Multi-View Diffusion ModelsRuiqi Gao, Aleksander Holynski, Philipp Henzler, Arthur Brussee et al.NeurIPS 2024 · 490 citations
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