Multi-view 3D Reconstruction by Fusing Polarization Information

For the shortcomings of current 3D reconstruction models such as poor reconstruction effect and blurred edges when dealing with weakly textured and textureless objects, this paper fuses the rich polarization spectral information with multi-view 3D reconstruction and presents the MP-mip-NeRf 360 model. This paper has constructed a multi-angle polarization dataset and systematic theoretical model validations are completed on this dataset. Compared with existing deep learning models, our model achieves better results in terms of accuracy, rendering more realistic scenes and obtaining more detailed depth maps.