ePBR: Extended PBR Materials in Image Synthesis

• URL: http://arxiv.org/abs/2504.17062v1
• Date: Wed, 23 Apr 2025 19:15:42 GMT
• Title: ePBR: Extended PBR Materials in Image Synthesis
• Authors: Yu Guo, Zhiqiang Lao, Xiyun Song, Yubin Zhou, Zongfang Lin, Heather Yu,
• Abstract summary: Intrinsic image representation offers a well-balanced trade-off, decomposing images into fundamental components.<n>We extend intrinsic image representations to incorporate both reflection and transmission properties.<n>With the Extended PBR (ePBR) Materials, we can effectively edit the materials with precise controls.
• Score: 2.3241174970798126
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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