mlsanityData to 7 Oct 2026

Eclipse: Disambiguating Illumination and Materials using Unintended Shadows

arXiv 2305.16321 ↗First posted 25 May 2023cs.CV cs.GRcited by 14

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Abstract (arXiv)

Decomposing an object's appearance into representations of its materials and the surrounding illumination is difficult, even when the object's 3D shape is known beforehand. This problem is especially challenging for diffuse objects: it is ill-conditioned because diffuse materials severely blur incoming light, and it is ill-posed because diffuse materials under high-frequency lighting can be indistinguishable from shiny materials under low-frequency lighting. We show that it is possible to recover precise materials and illumination -- even from diffuse objects -- by exploiting unintended shadows, like the ones cast onto an object by the photographer who moves around it. These shadows are a nuisance in most previous inverse rendering pipelines, but here we exploit them as signals that improve conditioning and help resolve material-lighting ambiguities. We present a method based on differentiable Monte Carlo ray tracing that uses images of an object to jointly recover its spatially-varying materials, the surrounding illumination environment, and the shapes of the unseen light occluders who inadvertently cast shadows upon it.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 19 of its 57 references that are in the map. First posted on arXiv 25 May 2023.

Builds on

19 of 57 references.

References · 19

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  3. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
  4. 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 569
  5. 2020NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesiscited by 493
  6. 2020NeRD: Neural Reflectance Decomposition from Image Collectionscited by 446
  7. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  8. 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 332
  9. 2019Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Imagecited by 202
  10. 2020Neural Reflectance Fields for Appearance Acquisitioncited by 196
  11. 2017Learning to Predict Indoor Illumination from a Single Imagecited by 160
  12. 2020Deep Reflectance Volumes: Relightable Reconstructions from Multi-View Photometric Imagescited by 98
7 more
  1. 2019DeepLight: Learning Illumination for Unconstrained Mobile Mixed Realitycited by 63
  2. 2019Neural Illumination: Lighting Prediction for Indoor Environmentscited by 57
  3. 2016Deep Outdoor Illumination Estimationcited by 53
  4. 2022NeROIC: Neural Rendering of Objects from Online Image Collectionscited by 36
  5. 2022Differentiable Rendering of Neural SDFs through Reparameterizationcited by 26
  6. 2020Seeing the World in a Bag of Chipscited by 25
  7. 2020Learning Illumination from Diverse Portraitscited by 15

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 7; 2025: 5; 2026: 1.

14 papers.

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