Multi View Inverse Rendering

Multi-view inverse rendering aims to reconstruct 3D scene properties—geometry, materials, and lighting—from multiple images taken from different viewpoints. Current research focuses on improving the accuracy and efficiency of this reconstruction, particularly by addressing challenges like shadow decomposition, handling complex lighting conditions (including spatially varying and global illumination), and mitigating ambiguities arising from multiple light bounces. This involves developing novel neural network architectures, often incorporating physically-based rendering models and advanced techniques like implicit lighting representations and polarization cues, to achieve more realistic and robust results. The advancements in this field have significant implications for applications such as virtual and augmented reality, material editing, and novel view synthesis.