Intrinsic Light Field Images
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Abstract (arXiv)
We present a method to automatically decompose a light field into its intrinsic shading and albedo components. Contrary to previous work targeted to 2D single images and videos, a light field is a 4D structure that captures non-integrated incoming radiance over a discrete angular domain. This higher dimensionality of the problem renders previous state-of-the-art algorithms impractical either due to their cost of processing a single 2D slice, or their inability to enforce proper coherence in additional dimensions. We propose a new decomposition algorithm that jointly optimizes the whole light field data for proper angular coherence. For efficiency, we extend Retinex theory, working on the gradient domain, where new albedo and occlusion terms are introduced. Results show our method provides 4D intrinsic decompositions difficult to achieve with previous state-of-the-art algorithms. We further provide a comprehensive analysis and comparisons with existing intrinsic image/video decomposition methods on light field images.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Aug 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1; 2025: 0; 2026: 1.
3 papers.
- 2021Single-image Full-body Human Relightingcited by 30
- 2024Surf-NeRF: Surface Regularised Neural Radiance Fieldscited by 3
- 2026Intrinsic decomposition and editing of 3D Gaussian splatscited by 0
- 2026Intrinsic decomposition and editing of 3D Gaussian splats30 Jun 2026
- 2024Surf-NeRF: Surface Regularised Neural Radiance Fields27 Nov 2024
- 2021Single-image Full-body Human Relighting15 Jul 2021