The field of 3D reconstruction and material analysis is rapidly evolving, with a focus on developing innovative methods for accurate and efficient reconstruction of complex scenes and objects. Recent developments have highlighted the importance of incorporating optical priors, such as polarization, to resolve photometric ambiguities and enhance reconstruction accuracy. Additionally, there is a growing trend towards automation, with methods being developed to automate the 3D scanning and reconstruction process, including the use of data-driven uncertainty quantification models. Noteworthy papers in this regard include PolarGS, which leverages polarization to resolve photometric ambiguities, and Auto3R, which automates 3D scanning and reconstruction via data-driven uncertainty quantification. Other notable papers, such as PolarGuide-GSDR and SurfFill, have also made significant contributions to the field, demonstrating the potential for real-time rendering and accurate reflection reconstruction. Overall, these advancements have the potential to revolutionize various fields, including architecture, engineering, and construction, by enabling the creation of highly accurate digital models of complex scenes and objects.