Image-to-Image Regression

Image-to-Image Regression is an important task in computer vision, aiming to predict continuous numerical attributes of output images from input images. The core objective of this technique is to establish a mapping relationship between input and output images, thereby achieving precise quantification of image features. Its application value is extensive, including but not limited to medical image analysis, remote sensing image processing, and environmental perception in autonomous driving systems, significantly enhancing the utilization efficiency of image data and decision accuracy.