Multi-times Monte Carlo Rendering for Inter-reflection Reconstruction
This work addresses a specific bottleneck in 3D reconstruction for reflective objects, which is incremental but important for applications like relighting and material editing.
The paper tackles the challenge of reconstructing reflective surfaces with inter-reflections in inverse rendering by proposing Ref-MC2, which uses multi-time Monte Carlo sampling and a specularity-adaptive strategy to improve accuracy and reduce computational complexity, outperforming other methods on a new dataset.
Inverse rendering methods have achieved remarkable performance in reconstructing high-fidelity 3D objects with disentangled geometries, materials, and environmental light. However, they still face huge challenges in reflective surface reconstruction. Although recent methods model the light trace to learn specularity, the ignorance of indirect illumination makes it hard to handle inter-reflections among multiple smooth objects. In this work, we propose Ref-MC2 that introduces the multi-time Monte Carlo sampling which comprehensively computes the environmental illumination and meanwhile considers the reflective light from object surfaces. To address the computation challenge as the times of Monte Carlo sampling grow, we propose a specularity-adaptive sampling strategy, significantly reducing the computational complexity. Besides the computational resource, higher geometry accuracy is also required because geometric errors accumulate multiple times. Therefore, we further introduce a reflection-aware surface model to initialize the geometry and refine it during inverse rendering. We construct a challenging dataset containing scenes with multiple objects and inter-reflections. Experiments show that our method outperforms other inverse rendering methods on various object groups. We also show downstream applications, e.g., relighting and material editing, to illustrate the disentanglement ability of our method.