We present MIRReS, a novel two-stage inverse rendering framework that jointly
reconstructs and optimizes the explicit geometry, material, and lighting from
multi-view images. Unlike previous methods that rely on implicit irradiance
fields or simplified path tracing algorithms, our method extracts an explicit
geometry (triangular mesh) in stage one, and introduces a more realistic
physically-based inverse rendering model that utilizes multi-bounce path
tracing and Monte Carlo integration. By leveraging multi-bounce path tracing,
our method effectively estimates indirect illumination, including
self-shadowing and internal reflections, which improves the intrinsic
decomposition of shape, material, and lighting. Moreover, we incorporate
reservoir sampling into our framework to address the noise in Monte Carlo
integration, enhancing convergence and facilitating gradient-based optimization
with low sample counts. Through qualitative and quantitative evaluation of
several scenarios, especially in challenging scenarios with complex shadows, we
demonstrate that our method achieves state-of-the-art performance on
decomposition results. Additionally, our optimized explicit geometry enables
applications such as scene editing, relighting, and material editing with
modern graphics engines or CAD software. The source code is available at
this https URL

MIRReS 是一个新颖的双阶段逆向渲染框架，通过联合重建和优化多视角图像中的显式几何、材质和光照，提供更真实的物理反渲染模型，包括多次反弹路径追踪和蒙特卡罗积分，有效估计间接照明，改善形状、材质和光照的内在分解，通过蓄水池抽样解决蒙特卡罗积分中的噪声问题，实现低样本数下的梯度优化，展示在复杂阴影场景中达到最先进的分解结果，并能在现代图形引擎或 CAD 软件中进行场景编辑、重新照明和材质编辑。