Systems and methods for predicting a depth map using diffusion-based modeling

Abstract

System, methods, and other embodiments described herein relate to estimating a depth map from an image using a diffusion model that efficiently learns in optimal computational spaces using a learning model and trains with sparse data. In one embodiment, a method includes estimating a local vector for an image by combining random noise, an image embedding about the image, and a geometric embedding using a learning model, the local vector having depth information at a pixel-level for the image. The method also includes predicting a global vector by combining the image embedding and the geometric embedding at a scene-level by the learning model. The method also includes inferring a depth map of the image by combining the local vector and the global vector using a diffusion model.