ePBR: Extended PBR Materials in Image Synthesis
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Abstract (arXiv)
Realistic indoor or outdoor image synthesis is a core challenge in computer vision and graphics. The learning-based approach is easy to use but lacks physical consistency, while traditional Physically Based Rendering (PBR) offers high realism but is computationally expensive. Intrinsic image representation offers a well-balanced trade-off, decomposing images into fundamental components (intrinsic channels) such as geometry, materials, and illumination for controllable synthesis. However, existing PBR materials struggle with complex surface models, particularly high-specular and transparent surfaces. In this work, we extend intrinsic image representations to incorporate both reflection and transmission properties, enabling the synthesis of transparent materials such as glass and windows. We propose an explicit intrinsic compositing framework that provides deterministic, interpretable image synthesis. With the Extended PBR (ePBR) Materials, we can effectively edit the materials with precise controls.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 28 of its 55 references that are in the map. First posted on arXiv 23 Apr 2025.
Builds on
28 of 55 references.
References · 28
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
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- 2024Diffusion Model-Based Image Editing: A Surveycited by 212
- 2019Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Imagecited by 203
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- 2024RGBleftrightarrowX: Image decomposition and synthesis using material- and lighting-aware diffusion modelscited by 161
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- 2018Single-Image SVBRDF Capture with a Rendering-Aware Deep Networkcited by 116
16 more
- 2022Learning-based Inverse Rendering of Complex Indoor Scenes with Differentiable Monte Carlo Raytracingcited by 78
- 2023Intrinsic Image Diffusion for Indoor Single-view Material Estimationcited by 73
- 2024Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materialscited by 66
- 2023DiffusionLight: Light Probes for Free by Painting a Chrome Ballcited by 64
- 2025DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Modelscited by 57
- 2023Intrinsic Image Decomposition via Ordinal Shadingcited by 53
- 2024DreamMat: High-quality PBR Material Generation with Geometry- and Light-aware Diffusion Modelscited by 50
- 2024Colorful Diffuse Intrinsic Image Decomposition in the Wildcited by 44
- 2023Alchemist: Parametric Control of Material Properties with Diffusion Modelscited by 38
- 2020MaterialGAN: Reflectance Capture using a Generative SVBRDF Modelcited by 33
- 2024Material Anything: Generating Materials for Any 3D Object via Diffusioncited by 31
- 2024Boosting 3D Object Generation through PBR Materialscited by 10
- 2025Materialist: Physically Based Editing Using Single-Image Inverse Renderingcited by 10
- 2024MCMat: Multiview-Consistent and Physically Accurate PBR Material Generationcited by 9
- 2021SpongeCake: A Layered Microflake Surface Appearance Modelcited by 5
- 2025Single-image Reflectance and Transmittance Estimation from Any Flatbed Scannercited by 1
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.