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Accurate height estimation from monocular aerial imagery presents asignificant challenge due to its inherently ill-posed nature. This limitationis rooted in the absence of adequate geometric constraints available to themodel when training with monocular imagery. Without additional geometricinformation to supplement the monocular image data, the model's ability toprovide reliable estimations is compromised.  In this paper, we propose a method that enhances monocular height estimationby incorporating street-view images. Our insight is that street-view imagesprovide a distinct viewing perspective and rich structural details of thescene, serving as geometric constraints to enhance the performance of monocularheight estimation. Specifically, we aim to optimize an implicit 3D scenerepresentation, density field, with geometry constraints from street-viewimages, thereby improving the accuracy and robustness of height estimation. Ourexperimental results demonstrate the effectiveness of our proposed method,outperforming the baseline and offering significant improvements in terms ofaccuracy and structural consistency.

Enhancing Monocular Height Estimation from Aerial Images with Street-view Images