UTexGen: High‐quality texture reconstruction for large‐scale scenes using multi‐view images

Abstract When reconstructing extensive terrain, it is essential to partition it into smaller tiles for individual processing. This paper introduces a texture reconstruction approach that ensures seamless and consistent final outputs, even when processed tile by tile. Among the stages of multi‐view image‐based reconstruction, texture reconstruction presents significant challenges during tile‐based processing. Relying solely on local tile‐level data complicates achieving precise texture mapping. The absence of occlusion details between tiles can lead to selecting incorrect images as the best visible ones or adjusting tile texture colors differently, resulting in noticeable grid‐like texture seams in the final result. To mitigate these issues, we leverage global depth maps to accurately detect occlusions between neighboring tiles. Furthermore, by utilizing a shared texture candidate list, we establish uniform targets for texture color correction across tiles. Experimental findings demonstrate that leveraging global information for texture reconstruction on a tile‐by‐tile basis enables the creation of smooth and realistic texture maps, as validated through comparisons with existing methodologies.