mlsanityData to 14 Oct 2026

SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering

arXiv 2212.04968 ↗First posted 9 Dec 2022cs.CVcited by 6

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Abstract (arXiv)

We propose an end-to-end inverse rendering pipeline called SupeRVol that allows us to recover 3D shape and material parameters from a set of color images in a super-resolution manner. To this end, we represent both the bidirectional reflectance distribution function (BRDF) and the signed distance function (SDF) by multi-layer perceptrons. In order to obtain both the surface shape and its reflectance properties, we revert to a differentiable volume renderer with a physically based illumination model that allows us to decouple reflectance and lighting. This physical model takes into account the effect of the camera's point spread function thereby enabling a reconstruction of shape and material in a super-resolution quality. Experimental validation confirms that SupeRVol achieves state of the art performance in terms of inverse rendering quality. It generates reconstructions that are sharper than the individual input images, making this method ideally suited for 3D modeling from low-resolution imagery.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 48 of its 84 references that are in the map. First posted on arXiv 9 Dec 2022.

Builds on

48 of 84 references.

References · 48

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36 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 1.

6 papers.

  1. 2024Sparse Views, Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereocited by 6
  2. 2024PIR: Photometric Inverse Rendering with Shading Cues Modeling and Surface Reflectance Regularizationcited by 2
  3. 2025ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail Transfercited by 2
  4. 2025On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approachescited by 2
  5. 2024Incorporating dense metric depth into neural 3D representations for view synthesis and relightingcited by 0
  6. 2026DIAMOND-SSS: Diffusion-Augmented Multi-View Optimization for Data-efficient SubSurface Scatteringcited by 0