Shape From Tracing: Towards Reconstructing 3D Object Geometry and SVBRDF Material from Images via Differentiable Path Tracing
Not on the map. Why?
Abstract (arXiv)
Reconstructing object geometry and material from multiple views typically requires optimization. Differentiable path tracing is an appealing framework as it can reproduce complex appearance effects. However, it is difficult to use due to high computational cost. In this paper, we explore how to use differentiable ray tracing to refine an initial coarse mesh and per-mesh-facet material representation. In simulation, we find that it is possible to reconstruct fine geometric and material detail from low resolution input views, allowing high-quality reconstructions in a few hours despite the expense of path tracing. The reconstructions successfully disambiguate shading, shadow, and global illumination effects such as diffuse interreflection from material properties. We demonstrate the impact of different geometry initializations, including space carving, multi-view stereo, and 3D neural networks. Finally, with input captured using smartphone video and a consumer 360? camera for lighting estimation, we also show how to refine initial reconstructions of real-world objects in unconstrained environments.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Dec 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 2; 2022: 3; 2023: 2; 2024: 1; 2025: 1; 2026: 1.
10 papers.
- 2021NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illuminationcited by 135
- 2021DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderercited by 52
- 2022A Level Set Theory for Neural Implicit Evolution under Explicit Flowscited by 42
- 2022Neural Radiance Transfer Fields for Relightable Novel-view Synthesis with Global Illuminationcited by 41
- 2023NeMF: Inverse Volume Rendering with Neural Microflake Fieldcited by 34
- 2023IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracingcited by 20
- 2024Surfel-based Gaussian Inverse Rendering for Fast and Relightable Dynamic Human Reconstruction from Monocular Videocited by 12
- 2025ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail Transfercited by 2
- 2022Deep scene-scale material estimation from multi-view indoor capturescited by 0
- 2026Meshtryoshka: Differentiable Rendering of Real-World Scenes via Mesh Rasterizationcited by 0
- 2026Meshtryoshka: Differentiable Rendering of Real-World Scenes via Mesh Rasterization26 Jun 2026
- 2025ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail Transfer30 Jan 2025
- 2024Surfel-based Gaussian Inverse Rendering for Fast and Relightable Dynamic Human Reconstruction from Monocular Video21 Jul 2024
- 2023IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing8 Dec 2023
- 2023NeMF: Inverse Volume Rendering with Neural Microflake Field3 Apr 2023
- 2022Deep scene-scale material estimation from multi-view indoor captures15 Nov 2022
- 2022Neural Radiance Transfer Fields for Relightable Novel-view Synthesis with Global Illumination27 Jul 2022
- 2022A Level Set Theory for Neural Implicit Evolution under Explicit Flows14 Apr 2022
- 2021DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer30 Oct 2021
- 2021NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination3 Jun 2021