Cross View Image To Image Translation

Cross-View Image-to-Image Translation is a computer vision technique aimed at learning the mapping relationship between different views or modalities to achieve image conversion from one view or modality to another. The goal of this technology is to generate high-quality and semantically consistent images in the target domain, thereby enhancing data diversity and improving model generalization capabilities. Its application value is extensive, including but not limited to medical image analysis, remote sensing image processing, and environmental perception in autonomous driving systems, effectively addressing the issue of insufficient cross-domain data and promoting the integration and utilization of multi-modal data.